yusuke1997/dblp-id-title huggingface dataset:
Performance and impact analysis of key structural parameters of hot in-place recycling equipments used on hot-air circulated asphalt road
Dynamic and fine-grained authentication and authorisation for grid computing
Forest fire essentials: a cellular automaton-wise, percolation-oriented model
Prediction of COVID-19 spread in world using pandemic dataset with application of auto ARIMA and SIR models
Using PRTR database for the assessment of surface water risk and improvement of monitoring in Japan
Examining metrics and methods for determining critical facility system effectiveness
Resilient industrial control systems based on multiple redundancy
An approach to identifying geographic interdependencies among critical infrastructures
Efficient Marine Debris Infrastructures on Optimising SVM with LoG Segmentation for Enhanced IoR, DC and Hausdorff Distance Performances
Flight-delay propagation, allowing for behavioural response
A review on smart water management in various domestic areas: an approach for water consumption and leakage perspectives
Urban infrastructure financing in India: a proposed framework for ULBs
Ensemble Machine Learning Regression Technique to Select the Type of Concrete as Radiation Shielding Material
Hosting critical infrastructure services in the cloud environment considerations
Failure modes and effects analysis for an engineering design modification in the US nuclear power industry
3D simulation research on the damage of load-bearing structure of prefabricated building based on BIM model
Network security mechanisms utilising network address translation
Project planning and monitoring analysis for sustainable environment and power infrastructure project development in Lagos State, Nigeria
A construction schedule management method of large-scale construction project based on BIM model
A prospective study of the determinants of economic growth in Tunisia 1990-2030
Data augmentation for numerical data from manufacturing processes: an overview of techniques and assessment of when which techniques work
Employing machine learning in water infrastructure management: predicting pipeline failures for improved maintenance and sustainable operations
Modular stochastic configuration network prediction interval for furnace temperature in municipal solid waste incineration
E-MobileViT: a lightweight model for traffic sign recognition
Masked autoencoder: influence of self-supervised pretraining on object segmentation in industrial images
Using the fuzzy integrals for the ensemble-based segmentation of asphalt cracks
Orthogonal stochastic configuration networks with adaptive construction parameter for data analytics
On the robustness of vision transformers for in-flight monocular depth estimation
Working condition recognition of fused magnesium furnace based on stochastic configuration networks and reinforcement learning
Modeling and parameter identification of verification systems using stochastic configuration networks
A case weighted similarity deep measurement method based on a self-attention Siamese neural network
The role of generative artificial intelligence (GAI) in customer personalisation (CP) development in SMEs: a theoretical framework and research propositions
𝕋 2 Net: an improved image-based text transfer framework using background inpainting and text conversion
A robust transfer deep stochastic configuration network for industrial data modeling
Efficiency optimization methods for stochastic configuration networks
A mathematical model for efficient extraction of key locations from point-cloud data in track area
FSL: federated sequential learning-based cyberattack detection for Industrial Internet of Things
A stochastic configuration networks-based nonsingular fast terminal sliding mode control approach for indirect matrix converter-driven permanent magnet linear synchronous motors
Approach to provide interpretability in machine learning models for image classification
Modified genetic algorithm to solve worker assignment problem with time windows
Surrogate-assisted evolutionary multi-objective optimisation of office building glazing
Comparison and assessment of machine learning approaches in manufacturing applications
Perfednilm: a practical personalized federated learning-based non-intrusive load monitoring
Gene expression model inference from snapshot RNA data using Bayesian non-parametrics
Combining computational controls with natural text reveals aspects of meaning composition
MetaKSSD: boosting the scalability of the reference taxonomic marker database and the performance of metagenomic profiling using sketch operations
Gaps in gender and socioeconomic mobility disparity studies
Efficient sampling of high-dimensional free energy landscapes using adaptive reinforced dynamics
A rigid body framework for multicellular modeling
Solving the electronic Schrödinger equation for multiple nuclear geometries with weight-sharing deep neural networks
Designing equitable algorithms
Fast and accurate bootstrap confidence limits on genome-scale phylogenies using little bootstraps
A scalable framework for learning the geometry-dependent solution operators of partial differential equations
Spin-symmetry-enforced solution of the many-body Schrödinger equation with a deep neural network
Shuffling haplotypes to share reference panels for imputation
An automated framework for high-throughput predictions of NMR chemical shifts within liquid solutions
Fast multi-source nanophotonic simulations using augmented partial factorization
Unified deep learning framework for many-body quantum chemistry via Green's functions
Identifying variants of molecules through database search of mass spectra
Enhancing structured light with optimized metasurfaces
Digital twins in mechanical and aerospace engineering
Experts go deeper
Decoding reward-curiosity conflict in decision-making from irrational behaviors
Multi-task learning for medical foundation models
Publisher Correction: Maximally localized dynamical quantum embedding for solving many-body correlated systems
Efficient simulations of electronic spectra
The decomposition of perturbation modeling
Advancing the science of synthesis
Author Correction: Deep-learning electronic-structure calculation of magnetic superstructures
On the cost-accuracy trade-off in electrolytes
Parameter inference for systems biology models
Computationally guided zeolite phase control
Evolving scattering networks for engineering disorder
Uncovering cell identity through differential stability with Cepo
Opportunities in full-stack design of low-overhead fault-tolerant quantum computation
Enhancing protein stability prediction with geometric learning and pre-training strategies
Detecting context-dependent gene regulation
Dos and don'ts in a cover letter
Reinstating functionality of complex systems
Bio-inspired adaptive grasper by chiral wrinkling
From data to conservation laws
A graph neural network for predicting the adsorption energy of molecules on metal surfaces
Computational design of quantum defects in two-dimensional materials
Dynamic visualization of high-dimensional data
Quantifying batch effects for individual genes in single-cell data
Accurate transition state generation with an object-aware equivariant elementary reaction diffusion model
Electron density-based GPT for optimization and suggestion of host-guest binders
Programmable responsive metamaterials for mechanical computing and robotics
Publisher Correction: A perspective on brain-age estimation and its clinical promise
Making light work of hydride transfer
Interpretable model of CRISPR-Cas9 enzymatic reactions
A look into our non-primary formats
Scalable optical learning operator
Revisiting colocalization via optimal transport
Taking a deep dive with active learning for drug discovery
Moving towards better communication
Flipping the intuition for games on dynamic networks
Learning to decode logical circuits
Theorists and experimentalists must join forces
Predicting the regulatory impacts of noncoding variants on gene expression through epigenomic integration across tissues and single-cell landscapes
Consistent cross-modal identification of cortical neurons with coupled autoencoders
Building molecules across the periodic table
SimuCell3D: three-dimensional simulation of tissue mechanics with cell polarization
Proteoform search from protein database with top-down mass spectra
Guided diffusion for inverse molecular design
Simulating fluids, gases and everything in between
Pioneering quantum information science
An invitation to social scientists
Deep-learning electronic-structure calculation of magnetic superstructures
Comprehensive prediction and analysis of human protein essentiality based on a pretrained large language model
Meet the editors
Boosting crystal structure prediction via symmetry
Xeric plants inspire adaptable liquid crystal elastomers for water collection
Discrete latent embedding of single-cell chromatin accessibility sequencing data for uncovering cell heterogeneity
Towards a consistent neuron classification
Theoretical insights into single-atom catalysts
Quantum embedding theories to simulate condensed systems on quantum computers
Microbial community dynamics revisited
Accelerating the design of compositionally complex materials via physics-informed artificial intelligence
Strategy evolution on higher-order networks
Extracting insights from heterogeneous tissues
The role of computational science in digital twins
Multi-view manifold learning of human brain-state trajectories
Experimental quantum adversarial learning with programmable superconducting qubits
Mixed model-based deconvolution of cell-state abundances (MeDuSA) along a one-dimensional trajectory
Metamaterials design via and for computation
Memory and computation together at last
Modeling galvanostatic charge-discharge of nanoporous supercapacitors
Artificial agents that negotiate and reach agreements
Geometry and symmetry-breaking in cell polarity
The increasing potential and challenges of digital twins
Investigating open reading frames in known and novel transcripts using ORFanage
Probing the limitations of multimodal language models for chemistry and materials research
Computational challenges in numerical relativity in the gravitational-wave era
Insights on protein condensate formation
Predicting protein structure from single sequences
Escaping the local catalytic activity space
Using labels to limit AI misuse in health
Making the most of presubmission enquiries
Current and future machine learning approaches for modeling atmospheric cluster formation
Synthesizing domain science with machine learning
Effect of spatial sampling on phylogeography
Expanding materials science with universal many-body graph neural networks
Porting software without affecting scientific results
Uncovering the genetic circuits that drive diseases
Acing the peer review process
Free-form metamaterials design with isotropic materials
Evolution of cooperation through cumulative reciprocity
Exploring the role of metamaterials in achieving advantage in optical computing
A full-stack platform for spiking deep learning
Digital twins in medicine
Traversing chemical space with active deep learning for low-data drug discovery
Cellular scale modeling of cytoskeletal assemblies
Cartographs enable interpretation of complex network visualizations
Treating quantum states as human faces
The fast continuous wavelet transformation (fCWT) for real-time, high-quality, noise-resistant time-frequency analysis
Large language model for molecular chemistry
Quantum harmonic free energies for biomolecules and nanomaterials
Efficient algorithms for the surface density of states in topological photonic and acoustic systems
Efficient large language model with analog in-memory computing
Extracting, filtering and simulating cellular barcodes using CellBarcode tools
Batch-effect correction with sample remeasurement in highly confounded case-control studies
Advancing data compression via noise detection
Leveraging generative models with periodicity-aware, invertible and invariant representations for crystalline materials design
Harnessing the power of emerging computational capabilities for independent mobility for persons with disabilities
Mining literature for perovskite solar cells
Author Correction: Deep-learning density functional theory Hamiltonian for efficient ab initio electronic-structure calculation
Enhancing discovery of host-guest binders
Toward a unified benchmark and framework for deep learning-based prediction of nuclear magnetic resonance chemical shifts
A pandemic's trajectory using PCR testing
Improving lab-of-origin prediction of genetically engineered plasmids via deep metric learning
Larger language models better align with the reading brain
AI for resource-constrained medical fields
Fast evaluation of the adsorption energy of organic molecules on metals via graph neural networks
A survival model generalized to regression learning algorithms
The whole picture in digital pathology
A machine learning algorithm for studying how molecules self-assemble and function
Moiré magnetic exchange interactions in twisted magnets
Pitfalls and prospects of quantum machine learning
Trials for computational psychiatry
Cover runners-up of 2022
Uncovering contaminants via machine learning
Learning about few-shot concept learning
Unifying structural descriptors for biological and bioinspired nanoscale complexes
Mapping disease regulatory circuits at cell-type resolution from single-cell multiomics data
Bridging the gap between artificial intelligence and natural intelligence
Predicting emerging drug interactions using GNNs
Machine learning speeds up genetic structure analysis
A simulated C. elegans with biophysically detailed neurons and muscle dynamics
Promises and perils of computational materials databases
Post-transplant dynamic risk prediction
Simultaneously improving reaction coverage and computational cost in automated reaction prediction tasks
Explainable neural networks that simulate reasoning
Predicting electronic structure calculation results
Shedding light on spatial signal transduction in cells using computational simulations
Bridging the gap in electronic structure calculations via machine learning
Efficiently pruning brain connectomes
Teaching spin symmetry while learning neural network wave functions
On the compatibility of generative AI and generative linguistics
Efficiently decoding quantum errors with machine learning
Transferable neural wavefunctions for solids
Probabilistic photonic computing for AI
Predicting oxidation states iteratively
Author Correction: Forced and spontaneous symmetry breaking in cell polarization
Machine learning speeds up search for surface structure
Defect graph neural networks for materials discovery in high-temperature clean-energy applications
SciToolAgent: a knowledge-graph-driven scientific agent for multitool integration
Celebrating today, inspiring tomorrow
Single-cell meta-analysis of inflammatory bowel disease with scIBD
Towards programmed protein generation
Diffraction-limited molecular cluster quantification with Bayesian nonparametrics
ActiveSVM selects minimal gene sets from gene expression data
Neural ADMIXTURE for rapid genomic clustering
Impact of spillovers on technological changes
Physics-informed recurrent neural network for time dynamics in optical resonances
Identification and analysis of 3D pores in packed particulate materials
Dendritic excitability controls overdispersion
A single-cell transcriptomic meta-analysis platform for inflammatory bowel disease
Machine learning to guide mathematicians
The critical role of persistent disruption in advancing science
Computing electron dynamics in momentum space
Towards efficient and adaptive simulations for continuum physics
Defining shapes of two-dimensional crystals with undefinable edge energies
Dynamic flux balance analysis of whole-body metabolism for type 1 diabetes
Cluster learning-assisted directed evolution
Publisher Correction: Defining shapes of two-dimensional crystals with undefinable edge energies
GRAPE for fast and scalable graph processing and random-walk-based embedding
Digital twins in city planning
Future directions in human mobility science
Cover runners-up of 2021
Constructing custom thermodynamics using deep learning
Cellular harmonics for the morphology-invariant analysis of molecular organization at the cell surface
How to change harmful beliefs
Graph embedding enables cell identification from spatial transcripts
Transfer learning for metal-organic frameworks
Stable maintenance of hidden switches as a strategy to increase the gene expression stability
Deep Bayesian active learning using in-memory computing hardware
A nonlinear dimension for machine learning in optical disordered media
Nowcasting food security
Sensing the shape of functional proteins with topology
Pathway trajectory analysis with tensor imputation reveals drug-induced single-cell transcriptomic landscape
Accelerating predictions of electronic transport and superconductivity
Effective lifetime of non-equilibrium carriers in semiconductors from non-adiabatic molecular dynamics simulations
A computational approach to evaluate how molecular mechanisms impact large-scale brain activity
Insights into hippocampal network function
Recent achievements and conceptual challenges for urban digital twins
Network science to study the origins of life
The rise of large language models
Software in science is ubiquitous yet overlooked
Physics-based modeling in the new era of enzyme engineering
Advancements and challenges of digital twins in industry
Application of wavefunction methods to metals
Full-scale scaffold model of the human hippocampus CA1 area
Functional change along cellular trajectories
Gender and racial diversity socialization in science
Theory of overparametrization in quantum neural networks
Theory and experimentation to assess reactivity
Quantum approximate multi-objective optimization
A framework for data-driven solution and parameter estimation of PDEs using conditional generative adversarial networks
Comparing single-cell datasets
Urban dynamics through the lens of human mobility
To review or not to review
Refining the lens of DNA microscopy
Of data and transparency
Denoising sparse microbial signals from single-cell sequencing of mammalian host tissues
Designing molecules with autoencoder networks
Micro-level social structures and the success of COVID-19 national policies
Characterizing true quantum computing power
Applying weighted Cox regression to genome-wide association studies of time-to-event phenotypes
Accelerating protein sensor optimization with machine learning
Omics correlation for efficient network construction
Greener urban communities
A computational quest for a sustainable world
An organelle-agnostic image analysis tool
A statistical framework for multi-trait rare variant analysis in large-scale whole-genome sequencing studies
A key player in high-performance computing
A computational science perspective on the legal system
Bridge over troubled transcripts
Calculating effective carrier lifetimes in semiconductor crystals under realistic conditions
Systematic simulations and analysis of transition states using committor functions
From mechanistic insight towards clinical implementation using normative modeling
Drawing statistically valid conclusions with ML
Detection of war destruction from satellite images
Interrogation of clonal tracking data using barcodetrackR
Predictive analyses of regulatory sequences with EUGENe
How molecular changes impact brain states and whole-brain activity: a multiscale approach
Network cartographs for interpretable visualizations
Learning physical laws from observations of complex dynamics
Diving deep into zeolite space
Efficient simulators for multi-source nanophotonics
Improving the balance of trade-offs in multi-objective optimization with quantum computing
Publisher Correction: Joint inference of discrete cell types and continuous type-specific variability in single-cell datasets with MMIDAS
Predicting reactivity with a push from theory
Accuracy and fairness go hand in hand
Single-cell-specific drug activities are revealed by a tensor imputation algorithm
Efficient prediction of relative ligand binding affinity in drug discovery
The imperative of physics-based modeling and inverse theory in computational science
Coupling mechanics into membrane electrochemistry
When disruption endures
Machine-guided path sampling to discover mechanisms of molecular self-organization
Machine learning proved efficient
Mathematically probing membrane fluctuations
A deep manifold-regularized learning model for improving phenotype prediction from multi-modal data
Deep learning training dynamics analysis for single-cell data
Publisher Correction: Autonomous inference of complex network dynamics from incomplete and noisy data
Evolution through the lens of genetic codes
Adversarial domain translation networks for integrating large-scale atlas-level single-cell datasets
A complete photonic integrated neuron for nonlinear all-optical computing
Kinetics of amyloid β from deep learning
Exploring proton-coupled electron transfer at multiple scales
Code sharing in the spotlight
Automated discovery of fundamental variables hidden in experimental data
Author Correction: The Inflammatory Bowel Disease Transcriptome and Metatranscriptome Meta-Analysis (IBD TaMMA) framework
Minimal gene set discovery in single-cell mRNA-seq datasets with ActiveSVM
Guidelines for multi-fidelity Bayesian optimization of molecules and materials
And the Turing Award goes to..
A transferable recommender approach for selecting the best density functional approximations in chemical discovery
Quantifying spatial under-reporting disparities in resident crowdsourcing
Multiple haplotype reconstruction from allele frequency data
Bridging generations and cultures in mathematics and computer science
Computation empowers CRISPR discovery and technology
Simulating thermal physics on quantum computers
Gender inequality infiltrates the in silico modeling world
Rational design of mechanical metamaterials
Digital twins of Earth and the computing challenge of human interaction
Designing efficient urban bike path networks that meet the needs of cyclists
A universal programmable Gaussian boson sampler for drug discovery
A comprehensive mapping of zeolite-template chemical space
A large-scale replication of scenario-based experiments in psychology and management using large language models
Improving the prediction of protein stability changes upon mutations by geometric learning and a pre-training strategy
Accelerated mass spectra analysis
Improving segregation prediction
Integrating statistical physics and machine learning for combinatorial optimization
Memristors enabling probabilistic AI at the edge
Digging deeper into the gut microbiome
Making sense of bacterial toxin evolution
Revealing neurocognitive and behavioral patterns through unsupervised manifold learning of dynamic brain data
A new computational model for human navigation
The yin-yang codec for archival DNA storage
Inverse problem via a Bayesian approach
An algorithmic framework for synthetic cost-aware decision making in molecular design
Large-scale transport simulation by deep learning
Fighting hate speech and misinformation online
The impact of uncertainty on predictions of the CovidSim epidemiological code
Making complex systems computable
Mining the chemical space for new antibiotics
Using metric learning to identify the lab-of-origin of engineered DNA
Boosting simulation of quantum computers
MassiveFold: unveiling AlphaFold's hidden potential with optimized and parallelized massive sampling
Rapid assessment of T-cell receptor specificity of the immune repertoire
Progressive assembly of multi-domain protein structures from cryo-EM density maps
Arti-'fickle' intelligence: using LLMs as a tool for inference in the political and social sciences
Overcoming computational bottlenecks in large language models through analog in-memory computing
Protecting against racial bias in DNA databasing
Synergy between photonic metamaterials and AI
A consolidated framework for quantifying interaction dynamics
Physics-inspired model for online content dynamics
Engineering morphogenesis of cell clusters with differentiable programming