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Showing 101–150 of 464 papers

TitleStatusHype
Gemini: Dynamic Bias Correction for Autonomous Experimentation and Molecular SimulationCode1
Geometric Representation Condition Improves Equivariant Molecule GenerationCode1
HSG-12M: A Large-Scale Spatial Multigraph DatasetCode1
Constructing Custom Thermodynamics Using Deep LearningCode1
Applications of Gaussian Processes at Extreme Lengthscales: From Molecules to Black HolesCode1
Applications and Techniques for Fast Machine Learning in Science—0
Applications and Challenges of AI and Microscopy in Life Science Research: A Review—0
A Dynamic Framework for Semantic Grouping of Common Data Elements (CDE) Using Embeddings and Clustering—0
Accelerating Legacy Numerical Solvers by Non-intrusive Gradient-based Meta-solving—0
Adversarial Examples and the Deeper Riddle of Induction: The Need for a Theory of Artifacts in Deep Learning—0
Explaining dark matter halo density profiles with neural networks—0
Explain the Black Box for the Sake of Science: the Scientific Method in the Era of Generative Artificial Intelligence—0
Causal-Copilot: An Autonomous Causal Analysis Agent—0
Evaluating the Adversarial Robustness for Fourier Neural Operators—0
Advancing the Scientific Frontier with Increasingly Autonomous Systems—0
A Novel Kuhnian Ontology for Epistemic Classification of STM Scholarly Articles—0
Deep Symbolic Optimization: Reinforcement Learning for Symbolic Mathematics—0
A Novel Paradigm for Neural Computation: X-Net with Learnable Neurons and Adaptable Structure—0
Causal Relational Learning—0
Causal Structural Learning from Time Series: A Convex Optimization Approach—0
A Perspective on Symbolic Machine Learning in Physical Sciences—0
Evolvable Conditional Diffusion—0
Can Theoretical Physics Research Benefit from Language Agents?—0
CodeScientist: End-to-End Semi-Automated Scientific Discovery with Code-based Experimentation—0
Combinatorial Scientific Discovery: Finding New Concept Combinations Beyond Link Prediction—0
Conditional computation in neural networks: principles and research trends—0
Advancing AI-Scientist Understanding: Making LLM Think Like a Physicist with Interpretable Reasoning—0
Calibrating for the Future:Enhancing Calorimeter Longevity with Deep Learning—0
An ELIXIR scoping review on domain-specific evaluation metrics for synthetic data in life sciences—0
Accelerating Earth Science Discovery via Multi-Agent LLM Systems—0
Explainable AI needs formal notions of explanation correctness—0
Expressive Symbolic Regression for Interpretable Models of Discrete-Time Dynamical Systems—0
Building Machine Learning Challenges for Anomaly Detection in Science—0
ALMol: Aligned Language-Molecule Translation LLMs through Offline Preference Contrastive Optimisation—0
Ab-initio quantum chemistry with neural-network wavefunctions—0
Breaking Boundaries: Distributed Domain Decomposition with Scalable Physics-Informed Neural PDE Solvers—0
BrainSCUBA: Fine-Grained Natural Language Captions of Visual Cortex Selectivity—0
Adaptive Exact Learning of Decision Trees from Membership Queries—0
Efficient nonmyopic batch active search—0
Algorithms and Statistical Models for Scientific Discovery in the Petabyte Era—0
Aligning Generalisation Between Humans and Machines—0
Efficiently Discovering Locally Exceptional yet Globally Representative Subgroups—0
BLIAM: Literature-based Data Synthesis for Synergistic Drug Combination Prediction—0
Efficient nonmyopic active search with applications in drug and materials discovery—0
Enabling real-time multi-messenger astrophysics discoveries with deep learning—0
Active Measure Reinforcement Learning for Observation Cost Minimization—0
Beyond Regrets: Geometric Metrics for Bayesian Optimization—0
Artificial Intelligence for Pediatric Ophthalmology—0
Beyond Predictions in Neural ODEs: Identification and Interventions—0
Better Research Software Tools to Elevate the Rate of Scientific Discovery -- or why we need to invest in research software engineering—0
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