From the 1 of 25 linked papers with an AI index.
25 papers
IADD-TR: Intervention-Aware Dynamics Decoupling with Targeted Regularization for Model-Based Reinforcement Learning
Zefeng Liang, Jie Qiao, Ruichu Cai +2
Model-based reinforcement learning (MBRL), which learns environment dynamics to generate synthetic experience, is a promising approach to sample-efficient decision making. Numerous…
Local Causal Structure Learning in the Presence of Latent Variables and Selection Bias
Zheng Li, Hao Zhang, Ruxin Wang +3
Discovering the direct causes and effects of a target variable from observational data is a fundamental problem in causal discovery, with broad applications in domains such as gene…
CDFM: Towards a General-Purpose Causal Discovery Foundation Model
Jie Qiao, Ruichu Cai, Zijian Li +6
The paper proposes CDFM, a foundation model trained on synthetic causal graphs that can infer causal structures in a zero‑shot manner across diverse domains, using a variational fr…
Rethinking Zero-Shot Time Series Classification: From Task-specific Classifiers to In-Context Inference
Juntao Fang, Shifeng Xie, Shengbin Nie +7
The zero-shot evaluation of time series foundation models (TSFMs) for classification typically uses a frozen encoder followed by a task-specific classifier. However, this practice…
Advances in Temporal Point Processes: Bayesian, Neural, and LLM Approaches
Feng Zhou, Quyu Kong, Jie Qiao +3
Temporal point processes (TPPs) are stochastic process models used to characterize event sequences occurring in continuous time. Traditional statistical TPPs have a long-standing h…
Temporal Smoothness Doubly Robust Learning for Debiased Knowledge Tracing
Peilin Zhan, Wei Chen, Weilin Chen +2
Knowledge Tracing (KT) is fundamental to intelligent education systems, yet relies on educational logs that are selectively observed. The non-random nature of exercise recommendati…