From the 5 of 259 papers with an AI index.
37 citations
- Rice UniversityUS76 papers
- Texas A&M UniversityUS74 papers
- University of Illinois ChicagoUS74 papers
- Tsinghua UniversityCN73 papers
- Eötvös Loránd UniversityHU72 papers
- The Ohio State UniversityUS72 papers
- Sejong UniversityKR71 papers
- University of Science and Technology of ChinaCN71 papers
- Warsaw University of TechnologyPL71 papers
- Panjab UniversityIN70 papers
- South China Normal UniversityCN70 papers
- Wayne State UniversityUS70 papers
19 papers · 1 filter
SafeOR-Gym: A Benchmark Suite for Safe Reinforcement Learning Algorithms on Practical Operations Research Problems
Asha Ramanujam, Adam Elyoumi, Hao Chen +5
The paper introduces SafeOR-Gym, a benchmark suite of nine operations‑research environments designed to evaluate safe reinforcement learning algorithms on realistic planning and sc…
Sparse Autoencoders for Interpretable Out-of-Distribution Detection
Ayush Karmacharya, Luke Luschwitz, Lucia Romero +2
The paper proposes using sparse autoencoders to extract interpretable sparse features from intermediate neural network layers and defines an OOD detection score based on cosine sim…
NASDAQ: Normalized Observation Space Dynamics-Augmented Q-Learning
Xinwei Liu, Junyuan Liang, Zicong Hong +2
Augmenting model-free reinforcement learning (RL) with representations learned through observation dynamics prediction (observation-predictive RL) can improve sample efficiency and…
On the Oracle Complexity of Interpolation-Based Gradient Descent
Dongmin Lee, William Lu, Anuran Makur
Recent work on first-order optimizers for empirical risk minimization (ERM) has suggested that smoothness of ERM loss functions in the training data, rather than in the optimizatio…
Prior-Guided Multi-Omic Transformers for Single-Cell Gene Regulatory Network Inference
Tianyang Xu, Tianci Liu, Niraj Rayamajhi +4
Gene regulatory networks (GRNs) capture transcription factor-target interactions and are central to understanding cell-state regulation and disease. Reconstructing GRNs from paired…
DeepSeekMath Meets Order Book: Group-Aware Policy Optimization for High-Frequency Directional Trading
Sayak Charabarty, Souradip Pal
This paper studies reinforcement learning for high-frequency trading on limit order books by pairing an Order-Flow-based state model with policy-gradient methods. Instead of value-…