predictive modeling
Predictive modeling encompasses methods used to create models that can predict future outcomes based on historical data. It leverages statistical techniques and machine learning to inform decision-making across various industries.
- A Pre-training Framework for Relational Data with Information-theoretic Principles
- ContextAgent: Context-Aware Proactive LLM Agents with Open-world Sensory Perceptions
- LawShift: Benchmarking Legal Judgment Prediction Under Statute Shifts
- MedAgentBoard: Benchmarking Multi-Agent Collaboration with Conventional Methods for Diverse Medical Tasks
- OligoGym: Curated Datasets and Benchmarks for Oligonucleotide Drug Discovery
- On the Entropy Calibration of Language Models
- Partial Information Decomposition via Normalizing Flows in Latent Gaussian Distributions
- Single-pass Adaptive Image Tokenization for Minimum Program Search
- Zero-shot protein stability prediction by inverse folding models: a free energy interpretation