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Showing 301–350 of 464 papers

TitleStatusHype
Simulation-Based Parallel Training—0
Simulation Intelligence: Towards a New Generation of Scientific Methods—0
Smirk: An Atomically Complete Tokenizer for Molecular Foundation Models—0
Soft causal learning for generalized molecule property prediction: An environment perspective—0
Solving Online Resource-Constrained Scheduling for Follow-Up Observation in Astronomy: a Reinforcement Learning Approach—0
Solving Sparse Finite Element Problems on Neuromorphic Hardware—0
Structuring Scientific Innovation: A Framework for Modeling and Discovering Impactful Knowledge Combinations—0
SuperCode: Sustainability PER AI-driven CO-DEsign—0
SylloBio-NLI: Evaluating Large Language Models on Biomedical Syllogistic Reasoning—0
Symbol-based entity marker highlighting for enhanced text mining in materials science with generative AI—0
LucidAtlas: Learning Uncertainty-Aware, Covariate-Disentangled, Individualized Atlas Representations—0
The Future of Fundamental Science Led by Generative Closed-Loop Artificial Intelligence—0
The IBEX Imaging Knowledge-Base: A Community Resource Enabling Adoption and Development of Immunofluoresence Imaging Methods—0
The Impact of Large Language Models on Scientific Discovery: a Preliminary Study using GPT-4—0
Theory-guided Data Science: A New Paradigm for Scientific Discovery from Data—0
The Power of the Pareto Front: Balancing Uncertain Rewards for Adaptive Experimentation in scanning probe microscopy—0
The Use of AI-Robotic Systems for Scientific Discovery—0
To be or not to be an Integer? Encoding Variables for Mathematical Text—0
Topic Modeling and Link-Prediction for Material Property Discovery—0
To think inside the box, or to think out of the box? Scientific discovery via the reciprocation of insights and concepts—0
Toward a Cohesive AI and Simulation Software Ecosystem for Scientific Innovation—0
Toward a Team of AI-made Scientists for Scientific Discovery from Gene Expression Data—0
Toward Building Science Discovery Machines—0
Toward Human-AI Co-creation to Accelerate Material Discovery—0
Towards an AI co-scientist—0
Chemist-X: Large Language Model-empowered Agent for Reaction Condition Recommendation in Chemical Synthesis—0
Towards Explainable Artificial Intelligence (XAI): A Data Mining Perspective—0
Towards Foundational Models for Dynamical System Reconstruction: Hierarchical Meta-Learning via Mixture of Experts—0
Towards Generalist Biomedical AI—0
Towards scientific discovery with dictionary learning: Extracting biological concepts from microscopy foundation models—0
Towards Scientific Discovery with Generative AI: Progress, Opportunities, and Challenges—0
Towards Scientific Intelligence: A Survey of LLM-based Scientific Agents—0
Towards trustworthy explanations with gradient-based attribution methods—0
Transformers and Large Language Models for Chemistry and Drug Discovery—0
Transforming the Hybrid Cloud for Emerging AI Workloads—0
Trillion Parameter AI Serving Infrastructure for Scientific Discovery: A Survey and Vision—0
Tunnel Effects in Cognition: A new Mechanism for Scientific Discovery and Education—0
"Turing Tests" For An AI Scientist—0
Uncertainty in Additive Feature Attribution methods—0
Understanding complex crowd dynamics with generative neural simulators—0
Unifying Sequences, Structures, and Descriptions for Any-to-Any Protein Generation with the Large Multimodal Model HelixProtX—0
Unsupervised physics-informed disentanglement of multimodal data for high-throughput scientific discovery—0
Building high accuracy emulators for scientific simulations with deep neural architecture search—0
Using Artificial Intelligence to aid Scientific Discovery of Climate Tipping Points—0
Using Causal Discovery to Track Information Flow in Spatio-Temporal Data - A Testbed and Experimental Results Using Advection-Diffusion Simulations—0
Using generative AI to investigate medical imagery models and datasets—0
Validation of an LLM-based Multi-Agent Framework for Protein Engineering in Dry Lab and Wet Lab—0
Vertical Symbolic Regression—0
We Need Improved Data Curation and Attribution in AI for Scientific Discovery—0
WHAT TO DO IF SPARSE REPRESENTATION LEARNING FAILS UNEXPECTEDLY?—0
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