Split (1)

train · 300k rows

paper_url stringlengths 36 81	paper_title stringlengths 1 242 ⌀	paper_arxiv_id stringlengths 9 16 ⌀	paper_url_abs stringlengths 18 314	paper_url_pdf stringlengths 21 935 ⌀	repo_url stringlengths 26 200	is_official bool 2 classes	mentioned_in_paper bool 2 classes	mentioned_in_github bool 2 classes	framework stringclasses 9 values
https://paperswithcode.com/paper/odyssey-a-public-gpu-based-code-for-general	Odyssey: A Public GPU-Based Code for General-Relativistic Radiative Transfer in Kerr Spacetime	1601.02063	https://arxiv.org/abs/1601.02063v2	https://arxiv.org/pdf/1601.02063v2.pdf	https://github.com/LeonGeiger/Kerr	false	false	true	none
https://paperswithcode.com/paper/efficient-leave-one-out-cross-validation-for	Efficient leave-one-out cross-validation for Bayesian non-factorized normal and Student-t models	1810.10559	https://arxiv.org/abs/1810.10559v5	https://arxiv.org/pdf/1810.10559v5.pdf	https://github.com/paul-buerkner/psis-non-factorized-paper	true	true	false	none
https://paperswithcode.com/paper/automatic-post-editing-of-machine-translation	Automatic Post-Editing of Machine Translation: A Neural Programmer-Interpreter Approach	null	https://aclanthology.org/D18-1341	https://aclanthology.org/D18-1341.pdf	https://github.com/trangvu/ape-npi	false	false	false	tf
https://paperswithcode.com/paper/attngan-fine-grained-text-to-image-generation	AttnGAN: Fine-Grained Text to Image Generation with Attentional Generative Adversarial Networks	1711.10485	http://arxiv.org/abs/1711.10485v1	http://arxiv.org/pdf/1711.10485v1.pdf	https://github.com/bprabhakar/text-to-image	false	false	false	pytorch
https://paperswithcode.com/paper/photo-realistic-single-image-super-resolution	Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network	1609.04802	http://arxiv.org/abs/1609.04802v5	http://arxiv.org/pdf/1609.04802v5.pdf	https://github.com/2023-MindSpore-1/ms-code-210/tree/main/CSNL	false	false	false	mindspore
https://paperswithcode.com/paper/distilling-interpretable-models-into-human	Distilling Interpretable Models into Human-Readable Code	2101.08393	https://arxiv.org/abs/2101.08393v2	https://arxiv.org/pdf/2101.08393v2.pdf	https://github.com/google/pwlfit	true	true	false	none
https://paperswithcode.com/paper/wide-residual-networks	Wide Residual Networks	1605.07146	http://arxiv.org/abs/1605.07146v4	http://arxiv.org/pdf/1605.07146v4.pdf	https://github.com/epfl-ml-reproducers/subspace-attack-reproduction	false	false	true	pytorch
https://paperswithcode.com/paper/show-and-tell-lessons-learned-from-the-2015	Show and Tell: Lessons learned from the 2015 MSCOCO Image Captioning Challenge	1609.06647	http://arxiv.org/abs/1609.06647v1	http://arxiv.org/pdf/1609.06647v1.pdf	https://github.com/HughKu/Im2txt	false	false	true	tf
https://paperswithcode.com/paper/a-wavenet-for-speech-denoising	A Wavenet for Speech Denoising	1706.07162	http://arxiv.org/abs/1706.07162v3	http://arxiv.org/pdf/1706.07162v3.pdf	https://github.com/francesclluis/source-separation-wavenet	false	false	true	tf
https://paperswithcode.com/paper/stackgan-realistic-image-synthesis-with	StackGAN++: Realistic Image Synthesis with Stacked Generative Adversarial Networks	1710.10916	http://arxiv.org/abs/1710.10916v3	http://arxiv.org/pdf/1710.10916v3.pdf	https://github.com/Maymaher/StackGANv2	false	false	true	pytorch
https://paperswithcode.com/paper/towards-k-means-friendly-spaces-simultaneous	Towards K-means-friendly Spaces: Simultaneous Deep Learning and Clustering	1610.04794	http://arxiv.org/abs/1610.04794v2	http://arxiv.org/pdf/1610.04794v2.pdf	https://github.com/boyangumn/DCN	true	true	true	none
https://paperswithcode.com/paper/simulaqron-a-simulator-for-developing-quantum	SimulaQron - A simulator for developing quantum internet software	1712.08032	http://arxiv.org/abs/1712.08032v2	http://arxiv.org/pdf/1712.08032v2.pdf	https://github.com/quantumprotocolzoo/protocols	false	false	true	none
https://paperswithcode.com/paper/recipenlg-a-cooking-recipes-dataset-for-semi	RecipeNLG: A Cooking Recipes Dataset for Semi-Structured Text Generation	null	https://aclanthology.org/2020.inlg-1.4	https://aclanthology.org/2020.inlg-1.4.pdf	https://github.com/Glorf/recipenlg	false	false	false	pytorch
https://paperswithcode.com/paper/online-deep-learning-learning-deep-neural	Online Deep Learning: Learning Deep Neural Networks on the Fly	1711.03705	http://arxiv.org/abs/1711.03705v1	http://arxiv.org/pdf/1711.03705v1.pdf	https://github.com/LIBOL/ODL	false	false	true	pytorch
https://paperswithcode.com/paper/model-rubik-s-cube-twisting-resolution-depth	Model Rubik's Cube: Twisting Resolution, Depth and Width for TinyNets	2010.14819	https://arxiv.org/abs/2010.14819v2	https://arxiv.org/pdf/2010.14819v2.pdf	https://github.com/leondgarse/keras_cv_attention_models/tree/main/keras_cv_attention_models/mobilenetv3_family	false	false	false	tf
https://paperswithcode.com/paper/190600133	ArcticNet: A Deep Learning Solution to Classify Arctic Wetlands	1906.00133	https://arxiv.org/abs/1906.00133v1	https://arxiv.org/pdf/1906.00133v1.pdf	https://github.com/geekJZY/arcticnet	true	true	false	pytorch
https://paperswithcode.com/paper/multi-label-image-classification-via	Multi-Label Image Classification via Knowledge Distillation from Weakly-Supervised Detection	1809.05884	http://arxiv.org/abs/1809.05884v2	http://arxiv.org/pdf/1809.05884v2.pdf	https://github.com/Yochengliu/MLIC-KD-WSD	false	false	true	none
https://paperswithcode.com/paper/few-shot-learning-with-graph-neural-networks	Few-Shot Learning with Graph Neural Networks	1711.04043	http://arxiv.org/abs/1711.04043v3	http://arxiv.org/pdf/1711.04043v3.pdf	https://github.com/HoganZhang/few-shot-gnn	false	false	true	pytorch
https://paperswithcode.com/paper/generative-adversarial-networks	Generative Adversarial Networks	1406.2661	https://arxiv.org/abs/1406.2661v1	https://arxiv.org/pdf/1406.2661v1.pdf	https://github.com/syahdeini/gan	false	false	true	tf
https://paperswithcode.com/paper/mastering-chess-and-shogi-by-self-play-with-a	Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm	1712.01815	http://arxiv.org/abs/1712.01815v1	http://arxiv.org/pdf/1712.01815v1.pdf	https://github.com/Neo-The1/ThinkingTicTacToe	false	false	true	tf
https://paperswithcode.com/paper/focal-loss-for-dense-object-detection	Focal Loss for Dense Object Detection	1708.02002	http://arxiv.org/abs/1708.02002v2	http://arxiv.org/pdf/1708.02002v2.pdf	https://github.com/trongnghia00/darknet	false	false	true	none
https://paperswithcode.com/paper/semi-supervised-learning-with-ladder-networks	Semi-Supervised Learning with Ladder Networks	1507.02672	http://arxiv.org/abs/1507.02672v2	http://arxiv.org/pdf/1507.02672v2.pdf	https://github.com/brandonrobertz/AcademicUrlTitles	false	false	true	none
https://paperswithcode.com/paper/co-designing-for-a-hybrid-workplace	Co-designing for a Hybrid Workplace Experience in Software Development	2212.09638	https://arxiv.org/abs/2212.09638v1	https://arxiv.org/pdf/2212.09638v1.pdf	https://github.com/co-design-hybrid/co-design-hybrid	true	true	false	none
https://paperswithcode.com/paper/towards-automated-deep-learning-efficient	Towards Automated Deep Learning: Efficient Joint Neural Architecture and Hyperparameter Search	1807.06906	http://arxiv.org/abs/1807.06906v1	http://arxiv.org/pdf/1807.06906v1.pdf	https://github.com/arberzela/EfficientNAS	false	false	true	pytorch
https://paperswithcode.com/paper/statistical-parametric-speech-synthesis-using	Statistical Parametric Speech Synthesis Using Generative Adversarial Networks Under A Multi-task Learning Framework	1707.01670	http://arxiv.org/abs/1707.01670v2	http://arxiv.org/pdf/1707.01670v2.pdf	https://github.com/rickyHong/GANTTS-update-repl	false	false	true	pytorch
https://paperswithcode.com/paper/perfect-sampling-with-unitary-tensor-networks	Perfect Sampling with Unitary Tensor Networks	1201.3974	http://arxiv.org/abs/1201.3974v3	http://arxiv.org/pdf/1201.3974v3.pdf	https://github.com/0/itensor-linear-rotors	false	false	true	none
https://paperswithcode.com/paper/real-time-single-image-and-video-super	Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network	1609.05158	http://arxiv.org/abs/1609.05158v2	http://arxiv.org/pdf/1609.05158v2.pdf	https://github.com/Nhat-Thanh/ESPCN-Pytorch	false	false	true	pytorch
https://paperswithcode.com/paper/a-structured-matrix-factorization-framework	A structured matrix factorization framework for large scale calcium imaging data analysis	1409.2903	http://arxiv.org/abs/1409.2903v1	http://arxiv.org/pdf/1409.2903v1.pdf	https://github.com/YGUO29/FANTASIA-CaImAn	false	false	true	none
https://paperswithcode.com/paper/recent-trends-in-deep-learning-based-natural	Recent Trends in Deep Learning Based Natural Language Processing	1708.02709	http://arxiv.org/abs/1708.02709v8	http://arxiv.org/pdf/1708.02709v8.pdf	https://github.com/ridakadri14/AspectBasedSentimentAnalysis	false	false	true	tf
https://paperswithcode.com/paper/cvae-gan-fine-grained-image-generation	CVAE-GAN: Fine-Grained Image Generation through Asymmetric Training	1703.10155	http://arxiv.org/abs/1703.10155v2	http://arxiv.org/pdf/1703.10155v2.pdf	https://github.com/One-sixth/CVAE-GAN_tensorlayer	false	false	true	tf
https://paperswithcode.com/paper/liqui-a-software-design-architecture-and	LIQUi\|>: A Software Design Architecture and Domain-Specific Language for Quantum Computing	1402.4467	http://arxiv.org/abs/1402.4467v1	http://arxiv.org/pdf/1402.4467v1.pdf	https://github.com/hhy37/Liquid	false	false	true	none
https://paperswithcode.com/paper/quantum-algorithm-for-solving-linear-systems	Quantum algorithm for solving linear systems of equations	0811.3171	http://arxiv.org/abs/0811.3171v3	http://arxiv.org/pdf/0811.3171v3.pdf	https://github.com/hhy37/Liquid	false	false	true	none
https://paperswithcode.com/paper/automatic-inference-of-sound-correspondence	Automatic Inference of Sound Correspondence Patterns across Multiple Languages	null	https://aclanthology.org/J19-1004	https://aclanthology.org/J19-1004.pdf	https://github.com/lingpy/correspondence-pattern-paper	true	true	false	none
https://paperswithcode.com/paper/the-temporal-event-graph	The Temporal Event Graph	1706.02128	http://arxiv.org/abs/1706.02128v1	http://arxiv.org/pdf/1706.02128v1.pdf	https://github.com/empiricalstateofmind/eventgraphs	false	false	true	none
https://paperswithcode.com/paper/inverse-problems-in-asteroseismology	Inverse Problems in Asteroseismology	1808.06649	http://arxiv.org/abs/1808.06649v1	http://arxiv.org/pdf/1808.06649v1.pdf	https://github.com/earlbellinger/thesis	false	false	true	none
https://paperswithcode.com/paper/predictive-entropy-search-for-efficient	Predictive Entropy Search for Efficient Global Optimization of Black-box Functions	1406.2541	http://arxiv.org/abs/1406.2541v1	http://arxiv.org/pdf/1406.2541v1.pdf	https://github.com/chongkewu/PESC-HPC	false	false	true	none
https://paperswithcode.com/paper/tencent-ml-images-a-large-scale-multi-label	Tencent ML-Images: A Large-Scale Multi-Label Image Database for Visual Representation Learning	1901.01703	https://arxiv.org/abs/1901.01703v7	https://arxiv.org/pdf/1901.01703v7.pdf	https://github.com/Tencent/tencent-ml-images	true	true	true	tf
https://paperswithcode.com/paper/visual-relationship-detection-with-language-1	Visual Relationship Detection with Language prior and Softmax	1904.07798	http://arxiv.org/abs/1904.07798v1	http://arxiv.org/pdf/1904.07798v1.pdf	https://github.com/Jungjaewon/Visual-Relationship-Detection	false	false	true	caffe2
https://paperswithcode.com/paper/end-to-end-memory-networks	End-To-End Memory Networks	1503.08895	http://arxiv.org/abs/1503.08895v5	http://arxiv.org/pdf/1503.08895v5.pdf	https://github.com/dare0021/MemN2N_Bench	false	false	true	none
https://paperswithcode.com/paper/towards-high-performance-video-object	Towards High Performance Video Object Detection for Mobiles	1804.05830	http://arxiv.org/abs/1804.05830v1	http://arxiv.org/pdf/1804.05830v1.pdf	https://github.com/stanlee321/LightFlow-TensorFlow	false	false	true	tf
https://paperswithcode.com/paper/multimodal-word-distributions	Multimodal Word Distributions	1704.08424	https://arxiv.org/abs/1704.08424v2	https://arxiv.org/pdf/1704.08424v2.pdf	https://github.com/benathi/multisense-prob-fasttext	false	false	true	none
https://paperswithcode.com/paper/feature-importance-measure-for-non-linear	Feature Importance Measure for Non-linear Learning Algorithms	1611.07567	http://arxiv.org/abs/1611.07567v1	http://arxiv.org/pdf/1611.07567v1.pdf	https://github.com/mcvidomi/MFI	false	false	true	none
https://paperswithcode.com/paper/inference-of-stellar-parameters-from	Inference of stellar parameters from brightness variations	1805.04519	http://arxiv.org/abs/1805.04519v1	http://arxiv.org/pdf/1805.04519v1.pdf	https://github.com/mkness/ACFCannon	true	true	false	none
https://paperswithcode.com/paper/event-graphs-advances-and-applications-of	Event Graphs: Advances and Applications of Second-Order Time-Unfolded Temporal Network Models	1809.03457	http://arxiv.org/abs/1809.03457v1	http://arxiv.org/pdf/1809.03457v1.pdf	https://github.com/empiricalstateofmind/eventgraphs	true	true	true	none
https://paperswithcode.com/paper/separating-the-signal-from-the-noise-evidence	Separating the signal from the noise: Evidence for deceleration in old-age death rates	1707.09433	http://arxiv.org/abs/1707.09433v2	http://arxiv.org/pdf/1707.09433v2.pdf	https://github.com/dfeehan/oldage-paper-code-released	false	false	true	none
https://paperswithcode.com/paper/cnncnn-convolutional-decoders-for-image	CNN+CNN: Convolutional Decoders for Image Captioning	1805.09019	http://arxiv.org/abs/1805.09019v1	http://arxiv.org/pdf/1805.09019v1.pdf	https://github.com/qingzwang/GHA-ImageCaptioning	false	false	true	pytorch
https://paperswithcode.com/paper/spnets-differentiable-fluid-dynamics-for-deep	SPNets: Differentiable Fluid Dynamics for Deep Neural Networks	1806.06094	http://arxiv.org/abs/1806.06094v2	http://arxiv.org/pdf/1806.06094v2.pdf	https://github.com/cschenck/SmoothParticleNets	true	true	false	pytorch
https://paperswithcode.com/paper/deep-residual-learning-for-image-recognition	Deep Residual Learning for Image Recognition	1512.03385	http://arxiv.org/abs/1512.03385v1	http://arxiv.org/pdf/1512.03385v1.pdf	https://github.com/MindSpore-paper-code-3/code7/tree/main/FaceAttribute	false	false	false	mindspore
https://paperswithcode.com/paper/efficient-estimation-of-word-representations	Efficient Estimation of Word Representations in Vector Space	1301.3781	http://arxiv.org/abs/1301.3781v3	http://arxiv.org/pdf/1301.3781v3.pdf	https://github.com/palmagro/gg2vec	false	false	true	none
https://paperswithcode.com/paper/a-structured-self-attentive-sentence	A Structured Self-attentive Sentence Embedding	1703.03130	http://arxiv.org/abs/1703.03130v1	http://arxiv.org/pdf/1703.03130v1.pdf	https://github.com/hantek/SelfAttentiveSentEmbed	false	false	true	pytorch
https://paperswithcode.com/paper/focal-loss-for-dense-object-detection	Focal Loss for Dense Object Detection	1708.02002	http://arxiv.org/abs/1708.02002v2	http://arxiv.org/pdf/1708.02002v2.pdf	https://github.com/fizyr/keras-retinanet	false	false	true	tf
https://paperswithcode.com/paper/yolo9000-better-faster-stronger	YOLO9000: Better, Faster, Stronger	1612.08242	http://arxiv.org/abs/1612.08242v1	http://arxiv.org/pdf/1612.08242v1.pdf	https://github.com/vantupham/darknet	false	false	true	none
https://paperswithcode.com/paper/u-net-convolutional-networks-for-biomedical	U-Net: Convolutional Networks for Biomedical Image Segmentation	1505.04597	http://arxiv.org/abs/1505.04597v1	http://arxiv.org/pdf/1505.04597v1.pdf	https://github.com/muramasa8191/DeepLearning	false	false	true	tf
https://paperswithcode.com/paper/sgdr-stochastic-gradient-descent-with-warm	SGDR: Stochastic Gradient Descent with Warm Restarts	1608.03983	http://arxiv.org/abs/1608.03983v5	http://arxiv.org/pdf/1608.03983v5.pdf	https://github.com/Harshvardhan1/cyclic-learning-schedulers-pytorch	false	false	true	pytorch
https://paperswithcode.com/paper/spatiotemporal-multiplier-networks-for-video	Spatiotemporal Multiplier Networks for Video Action Recognition	null	http://openaccess.thecvf.com/content_cvpr_2017/html/Feichtenhofer_Spatiotemporal_Multiplier_Networks_CVPR_2017_paper.html	http://openaccess.thecvf.com/content_cvpr_2017/papers/Feichtenhofer_Spatiotemporal_Multiplier_Networks_CVPR_2017_paper.pdf	https://github.com/feichtenhofer/st-resnet	true	true	false	none
https://paperswithcode.com/paper/knowing-when-to-look-adaptive-attention-via-a	Knowing When to Look: Adaptive Attention via A Visual Sentinel for Image Captioning	1612.01887	http://arxiv.org/abs/1612.01887v2	http://arxiv.org/pdf/1612.01887v2.pdf	https://github.com/miroblog/AdaptiveAttention	false	false	true	pytorch
https://paperswithcode.com/paper/salient-object-detection-driven-by-fixation	Salient Object Detection Driven by Fixation Prediction	null	http://openaccess.thecvf.com/content_cvpr_2018/html/Wang_Salient_Object_Detection_CVPR_2018_paper.html	http://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_Salient_Object_Detection_CVPR_2018_paper.pdf	https://github.com/wenguanwang/ASNet	true	true	false	none
https://paperswithcode.com/paper/supervised-learning-of-universal-sentence	Supervised Learning of Universal Sentence Representations from Natural Language Inference Data	1705.02364	http://arxiv.org/abs/1705.02364v5	http://arxiv.org/pdf/1705.02364v5.pdf	https://github.com/facebookresearch/InferSent	true	true	true	pytorch
https://paperswithcode.com/paper/a-high-coverage-method-for-automatic-false	A High Coverage Method for Automatic False Friends Detection for Spanish and Portuguese	null	https://aclanthology.org/W18-3903	https://aclanthology.org/W18-3903.pdf	https://github.com/pln-fing-udelar/false-friends	true	true	false	none
https://paperswithcode.com/paper/the-chefs-hat-simulation-environment-for	The Chef's Hat Simulation Environment for Reinforcement-Learning-Based Agents	2003.05861	https://arxiv.org/abs/2003.05861v1	https://arxiv.org/pdf/2003.05861v1.pdf	https://github.com/pablovin/MoodyFramework	false	false	true	none
https://paperswithcode.com/paper/deep-video-deblurring	Deep Video Deblurring	1611.08387	http://arxiv.org/abs/1611.08387v1	http://arxiv.org/pdf/1611.08387v1.pdf	https://github.com/susomena/DeepSlowMotion	false	false	true	tf
https://paperswithcode.com/paper/adaptive-system-optimization-using-random	Adaptive system optimization using random directions stochastic approximation	1502.05577	http://arxiv.org/abs/1502.05577v2	http://arxiv.org/pdf/1502.05577v2.pdf	https://github.com/prashla/RDSA	true	true	false	none
https://paperswithcode.com/paper/identification-of-emergency-blood-donation	Identification of Emergency Blood Donation Request on Twitter	null	https://aclanthology.org/W18-5907	https://aclanthology.org/W18-5907.pdf	https://github.com/pmathur5k10/EBDR	true	true	false	none
https://paperswithcode.com/paper/rethinking-on-multi-stage-networks-for-human	Rethinking on Multi-Stage Networks for Human Pose Estimation	1901.00148	https://arxiv.org/abs/1901.00148v4	https://arxiv.org/pdf/1901.00148v4.pdf	https://github.com/chenyilun95/tf-cpn	false	false	true	tf
https://paperswithcode.com/paper/semantic-visual-navigation-by-watching	Semantic Visual Navigation by Watching YouTube Videos	2006.10034	https://arxiv.org/abs/2006.10034v2	https://arxiv.org/pdf/2006.10034v2.pdf	https://github.com/MatthewChang/video-dqn	true	false	false	pytorch
https://paperswithcode.com/paper/sound-event-detection-and-time-frequency	Sound Event Detection and Time-Frequency Segmentation from Weakly Labelled Data	1804.04715	http://arxiv.org/abs/1804.04715v2	http://arxiv.org/pdf/1804.04715v2.pdf	https://github.com/qiuqiangkong/sed_time_freq_segmentation	true	true	false	pytorch
https://paperswithcode.com/paper/dueling-network-architectures-for-deep	Dueling Network Architectures for Deep Reinforcement Learning	1511.06581	http://arxiv.org/abs/1511.06581v3	http://arxiv.org/pdf/1511.06581v3.pdf	https://github.com/prajwalgatti/DRL-Continuous-Control	false	false	true	none
https://paperswithcode.com/paper/very-deep-convolutional-networks-for-large	Very Deep Convolutional Networks for Large-Scale Image Recognition	1409.1556	http://arxiv.org/abs/1409.1556v6	http://arxiv.org/pdf/1409.1556v6.pdf	https://github.com/Tools4Project/4501Project	false	false	true	tf
https://paperswithcode.com/paper/efficient-training-of-energy-based-models-via	Efficient training of energy-based models via spin-glass control	1910.01592	https://arxiv.org/abs/1910.01592v4	https://arxiv.org/pdf/1910.01592v4.pdf	https://github.com/apozas/rapid	true	true	true	pytorch
https://paperswithcode.com/paper/context-dependent-fine-grained-entity-type	Context-Dependent Fine-Grained Entity Type Tagging	1412.1820	http://arxiv.org/abs/1412.1820v2	http://arxiv.org/pdf/1412.1820v2.pdf	https://github.com/shanzhenren/AFET	false	false	true	none
https://paperswithcode.com/paper/sampling-generative-networks	Sampling Generative Networks	1609.04468	http://arxiv.org/abs/1609.04468v3	http://arxiv.org/pdf/1609.04468v3.pdf	https://github.com/ptrblck/prog_gans_pytorch_inference	false	false	true	pytorch
https://paperswithcode.com/paper/breaking-the-curse-of-space-explosion-towards	Breaking the Curse of Space Explosion: Towards Efficient NAS with Curriculum Search	2007.07197	https://arxiv.org/abs/2007.07197v2	https://arxiv.org/pdf/2007.07197v2.pdf	https://github.com/guoyongcs/CNAS	true	true	false	pytorch
https://paperswithcode.com/paper/learning-imbalanced-datasets-with-label	Learning Imbalanced Datasets with Label-Distribution-Aware Margin Loss	1906.07413	https://arxiv.org/abs/1906.07413v2	https://arxiv.org/pdf/1906.07413v2.pdf	https://github.com/feidfoe/AdjustBnd4Imbalance	false	false	true	pytorch
https://paperswithcode.com/paper/learning-2d-temporal-adjacent-networks-for	Learning 2D Temporal Adjacent Networks for Moment Localization with Natural Language	1912.03590	https://arxiv.org/abs/1912.03590v3	https://arxiv.org/pdf/1912.03590v3.pdf	https://github.com/researchmm/2D-TAN	false	false	true	pytorch
https://paperswithcode.com/paper/multigrid-predictive-filter-flow-for	Multigrid Predictive Filter Flow for Unsupervised Learning on Videos	1904.01693	http://arxiv.org/abs/1904.01693v1	http://arxiv.org/pdf/1904.01693v1.pdf	https://github.com/bestaar/predictiveFilterFlow	false	false	true	pytorch
https://paperswithcode.com/paper/image-reconstruction-with-predictive-filter	Image Reconstruction with Predictive Filter Flow	1811.11482	http://arxiv.org/abs/1811.11482v1	http://arxiv.org/pdf/1811.11482v1.pdf	https://github.com/bestaar/predictiveFilterFlow	false	false	true	pytorch
https://paperswithcode.com/paper/revisiting-unreasonable-effectiveness-of-data	Revisiting Unreasonable Effectiveness of Data in Deep Learning Era	1707.02968	http://arxiv.org/abs/1707.02968v2	http://arxiv.org/pdf/1707.02968v2.pdf	https://github.com/Tencent/tencent-ml-images	false	false	true	tf
https://paperswithcode.com/paper/general-purpose-atomic-crosschain	General Purpose Atomic Crosschain Transactions	2011.12783	https://arxiv.org/abs/2011.12783v4	https://arxiv.org/pdf/2011.12783v4.pdf	https://github.com/ConsenSys/gpact	true	true	true	none
https://paperswithcode.com/paper/ms-dpps-multi-source-determinantal-point	MS-DPPs: Multi-Source Determinantal Point Processes for Contextual Diversity Refinement of Composite Attributes in Text to Image Retrieval	2507.06654	https://arxiv.org/abs/2507.06654v1	https://arxiv.org/pdf/2507.06654v1.pdf	https://github.com/nec-n-sogi/msdpp	true	true	true	pytorch
https://paperswithcode.com/paper/atlas-end-to-end-3d-scene-reconstruction-from	Atlas: End-to-End 3D Scene Reconstruction from Posed Images	2003.10432	https://arxiv.org/abs/2003.10432v3	https://arxiv.org/pdf/2003.10432v3.pdf	https://github.com/magicleap/Atlas	false	false	true	pytorch
https://paperswithcode.com/paper/nimbro-op2x-adult-sized-open-source-3d	NimbRo-OP2X: Adult-sized Open-source 3D Printed Humanoid Robot	1810.08395	http://arxiv.org/abs/1810.08395v1	http://arxiv.org/pdf/1810.08395v1.pdf	https://github.com/iswariyam/Mini-semantic-segmentation-network-pytorch	false	false	true	pytorch
https://paperswithcode.com/paper/invariance-analysis-of-saliency-models-versus	Invariance Analysis of Saliency Models versus Human Gaze During Scene Free Viewing	1810.04456	http://arxiv.org/abs/1810.04456v1	http://arxiv.org/pdf/1810.04456v1.pdf	https://github.com/CZHQuality/Sal-CFS-GAN	false	false	true	tf
https://paperswithcode.com/paper/unpaired-image-to-image-translation-using	Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks	1703.10593	https://arxiv.org/abs/1703.10593v7	https://arxiv.org/pdf/1703.10593v7.pdf	https://github.com/Shumway82/CycleGAN	false	false	true	tf
https://paperswithcode.com/paper/semi-supervised-learning-with-ladder-networks	Semi-Supervised Learning with Ladder Networks	1507.02672	http://arxiv.org/abs/1507.02672v2	http://arxiv.org/pdf/1507.02672v2.pdf	https://github.com/CuriousAI/ladder	false	false	true	none
https://paperswithcode.com/paper/bayesian-optimization-of-hyper-parameters-in	Bayesian optimization of hyper-parameters in reservoir computing	1611.05193	http://arxiv.org/abs/1611.05193v3	http://arxiv.org/pdf/1611.05193v3.pdf	https://github.com/rednotion/parallel_esn_web	false	false	true	none
https://paperswithcode.com/paper/convolutional-neural-network-architecture-for	Convolutional neural network architecture for geometric matching	1703.05593	http://arxiv.org/abs/1703.05593v2	http://arxiv.org/pdf/1703.05593v2.pdf	https://github.com/ignacio-rocco/cnngeometric_pytorch	false	false	true	pytorch
https://paperswithcode.com/paper/neural-audio-synthesis-of-musical-notes-with	Neural Audio Synthesis of Musical Notes with WaveNet Autoencoders	1704.01279	http://arxiv.org/abs/1704.01279v1	http://arxiv.org/pdf/1704.01279v1.pdf	https://github.com/NoaCahan/WavenetAutoEncoder	false	false	true	pytorch
https://paperswithcode.com/paper/tips-and-tricks-for-visual-question-answering	Tips and Tricks for Visual Question Answering: Learnings from the 2017 Challenge	1708.02711	http://arxiv.org/abs/1708.02711v1	http://arxiv.org/pdf/1708.02711v1.pdf	https://github.com/feifengwhu/question_attention	false	false	true	pytorch
https://paperswithcode.com/paper/retinal-vessel-segmentation-based-on-fully	Retinal vessel segmentation based on Fully Convolutional Neural Networks	1812.07110	http://arxiv.org/abs/1812.07110v2	http://arxiv.org/pdf/1812.07110v2.pdf	https://github.com/americofmoliveira/VesselSegmentation_ESWA	false	false	true	none
https://paperswithcode.com/paper/randomized-matrix-decompositions-using-r	Randomized Matrix Decompositions using R	1608.02148	http://arxiv.org/abs/1608.02148v4	http://arxiv.org/pdf/1608.02148v4.pdf	https://github.com/Benli11/ristretto	false	false	true	none
https://paperswithcode.com/paper/modified-shallow-water-equations-for	Modified Shallow Water Equations for significantly varying seabeds	1202.6542	http://arxiv.org/abs/1202.6542v6	http://arxiv.org/pdf/1202.6542v6.pdf	https://github.com/huwb/crest-oceanrender	false	false	true	none
https://paperswithcode.com/paper/semantic-document-distance-measures-and	Semantic Document Distance Measures and Unsupervised Document Revision Detection	1709.01256	http://arxiv.org/abs/1709.01256v2	http://arxiv.org/pdf/1709.01256v2.pdf	https://github.com/XiaofengZhu/wDTW-wTED	true	true	true	none
https://paperswithcode.com/paper/revisiting-decomposable-submodular-function	Revisiting Decomposable Submodular Function Minimization with Incidence Relations	1803.03851	http://arxiv.org/abs/1803.03851v3	http://arxiv.org/pdf/1803.03851v3.pdf	https://github.com/lipan00123/DSFM-with-incidence-relations	true	true	false	none
https://paperswithcode.com/paper/learning-deep-representations-of-fine-grained	Learning Deep Representations of Fine-grained Visual Descriptions	1605.05395	http://arxiv.org/abs/1605.05395v1	http://arxiv.org/pdf/1605.05395v1.pdf	https://github.com/Maymaher/StackGANv2	false	false	true	pytorch
https://paperswithcode.com/paper/an-end-to-end-trainable-neural-network-for	An End-to-End Trainable Neural Network for Image-based Sequence Recognition and Its Application to Scene Text Recognition	1507.05717	http://arxiv.org/abs/1507.05717v1	http://arxiv.org/pdf/1507.05717v1.pdf	https://github.com/bai-shang/crnn_ctc_ocr.Tensorflow	false	false	true	tf
https://paperswithcode.com/paper/learning-to-learn-without-forgetting-by	Learning to Learn without Forgetting by Maximizing Transfer and Minimizing Interference	1810.11910	https://arxiv.org/abs/1810.11910v3	https://arxiv.org/pdf/1810.11910v3.pdf	https://github.com/mattriemer/mer	true	true	false	pytorch
https://paperswithcode.com/paper/pythia-v01-the-winning-entry-to-the-vqa	Pythia v0.1: the Winning Entry to the VQA Challenge 2018	1807.09956	http://arxiv.org/abs/1807.09956v2	http://arxiv.org/pdf/1807.09956v2.pdf	https://github.com/songhe17/pythia-clone	false	false	true	pytorch
https://paperswithcode.com/paper/generative-adversarial-text-to-image	Generative Adversarial Text to Image Synthesis	1605.05396	http://arxiv.org/abs/1605.05396v2	http://arxiv.org/pdf/1605.05396v2.pdf	https://github.com/Maymaher/StackGANv2	false	false	true	pytorch
https://paperswithcode.com/paper/attngan-fine-grained-text-to-image-generation	AttnGAN: Fine-Grained Text to Image Generation with Attentional Generative Adversarial Networks	1711.10485	http://arxiv.org/abs/1711.10485v1	http://arxiv.org/pdf/1711.10485v1.pdf	https://github.com/Maymaher/StackGANv2	false	false	true	pytorch
https://paperswithcode.com/paper/benchmarking-machine-learning-models-on-eicu	Benchmarking machine learning models on multi-centre eICU critical care dataset	1910.00964	https://arxiv.org/abs/1910.00964v3	https://arxiv.org/pdf/1910.00964v3.pdf	https://github.com/mostafaalishahi/eICU_Benchmark	true	true	true	none

Subsets and Splits

Deduplicated Paper-Code Links

This query provides a detailed and organized list of repositories linked to single papers, highlighting official status and mention sources, which is useful for understanding the relationship between papers and their corresponding repositories.

Paper Repo Counts & Distribution

Provides detailed statistics on the distribution of papers across different numbers of repositories, highlighting the percentage of papers with multiple repositories.

Quantum Papers with Code Links

Lists quantum-related papers with their titles, arXiv IDs, frameworks, and code repository links, providing a valuable resource for researchers interested in quantum computing.

Financial Stock Price Prediction

Finds papers related to stock prices, financial markets, and predictions, providing a focused subset for further analysis.

Search for YOLO Links

Retrieves a limited set of records related to YOLO, providing basic information about papers and repositories but without deeper analysis.

Prompt Optimization and Personalization

Retrieves a limited set of papers with titles containing specific keywords related to prompt optimization and personalization, providing basic filtering of the dataset.