commit files to HF hub

papers.csv

@@ -825,7 +825,7 @@ Simplified Temporal Consistency Reinforcement Learning,"Yi Zhao, Wenshuai Zhao,
 A Robust Test for the Stationarity Assumption in Sequential Decision Making,"Jitao Wang, Chengchun Shi, Zhenke Wu",,,,,,,,,
 Maximal Initial Learning Rates in Deep ReLU Networks,"Gaurav Iyer, Boris Hanin, David Rolnick",http://arxiv.org/abs/2212.07295,,https://huggingface.co/papers/2212.07295,,,,2212.07295,3,0
 FAENet: Frame Averaging Equivariant GNNs for Materials Modeling,"ALEXANDRE DUVAL, Victor Schmidt, Alex Hernandez-Garcia, Fragkiskos Malliaros, Yoshua Bengio, Santiago Miret, David Rolnick",,,,,,,,,
-Stochastic Marginal Likelihood Gradients using Neural Tangent Kernels,"Alexander Immer, Tycho van der Ouderaa, Mark van der Wilk, Gunnar Ratsch, Bernhard Schölkopf",http://arxiv.org/abs/2306.03968,,https://huggingface.co/papers/2306.03968,,,,2306.03968,5,1
+Stochastic Marginal Likelihood Gradients using Neural Tangent Kernels,"Alexander Immer, Tycho van der Ouderaa, Mark van der Wilk, Gunnar Ratsch, Bernhard Schölkopf",http://arxiv.org/abs/2306.03968,,https://huggingface.co/papers/2306.03968,,,,2306.03968,5,2
 Single Point-Based Distributed Zeroth-Order Optimization with a Non-Convex Stochastic Objective Function,"Elissa Mhanna, Mohamad Assaad",,,,,,,,,
 On the Convergence of Gradient Flow on Multi-layer Linear Models,"Hancheng Min, Rene Vidal, Enrique Mallada",,,,,,,,,
 Towards Understanding and Reducing Graph Structural Noise for GNNs,"Mingze Dong, Yuval Kluger",,,,,,,,,
@@ -1018,7 +1018,7 @@ AdaptDiffuser: Diffusion Models as Adaptive Self-evolving Planners,"Zhixuan Lian
 Reinforcement Learning from Passive Data via Latent Intentions,"Dibya Ghosh, Chethan Bhateja, Sergey Levine",http://arxiv.org/abs/2304.04782,,https://huggingface.co/papers/2304.04782,,,,2304.04782,3,0
 Hierarchies of Reward Machines,"Daniel Furelos-Blanco, Mark Law, Anders Jonsson, Krysia Broda, Alessandra Russo",http://arxiv.org/abs/2205.15752,,https://huggingface.co/papers/2205.15752,,,,2205.15752,5,1
 Calibrating Multimodal Learning,"Huan Ma, qingyang zhang, Changqing Zhang, Bingzhe Wu, Huazhu Fu, Joey Tianyi Zhou, Qinghua Hu",http://arxiv.org/abs/2306.01265,,https://huggingface.co/papers/2306.01265,,,,2306.01265,6,0
-Cones: Concept Neurons in Diffusion Models for Customized Generation,"Zhiheng Liu, Ruili Feng, Kai Zhu, Yifei Zhang, Kecheng Zheng, Yu Liu, Deli Zhao, Jingren Zhou, Yang Cao",http://arxiv.org/abs/2303.05125,,https://huggingface.co/papers/2303.05125,,,,2303.05125,9,1
+Cones: Concept Neurons in Diffusion Models for Customized Generation,"Zhiheng Liu, Ruili Feng, Kai Zhu, Yifei Zhang, Kecheng Zheng, Yu Liu, Deli Zhao, Jingren Zhou, Yang Cao",http://arxiv.org/abs/2303.05125,,https://huggingface.co/papers/2303.05125,,,,2303.05125,9,2
 Continuation Path Learning for Homotopy Optimization,"Xi Lin, Zhiyuan Yang, Xiaoyuan Zhang, Qingfu Zhang",,,,,,,,,
 "Inflow, Outflow, and Reciprocity in Machine Learning","Mukund Sundararajan, Walid Krichene",,,,,,,,,
 Transformers Learn In-Context by Gradient Descent,"Johannes Von Oswald, Eyvind Niklasson, Ettore Randazzo, Joao Sacramento, Alexander Mordvintsev, Andrey Zhmoginov, Max Vladymyrov",http://arxiv.org/abs/2212.07677,https://github.com/google-research/self-organising-systems/tree/master/transformers_learn_icl_by_gd,https://huggingface.co/papers/2212.07677,,,,2212.07677,7,1