ICML 2024 Oral Papers
139 papers found • Page 1 of 3
$S^2$IP-LLM: Semantic Space Informed Prompt Learning with LLM for Time Series Forecasting
Zijie Pan, Yushan Jiang, Sahil Garg et al.
Adapting Static Fairness to Sequential Decision-Making: Bias Mitigation Strategies towards Equal Long-term Benefit Rate
Yuancheng Xu, Chenghao Deng, Yanchao Sun et al.
Adaptive Accompaniment with ReaLchords
Yusong Wu, Tim Cooijmans, Kyle Kastner et al.
A decoder-only foundation model for time-series forecasting
Abhimanyu Das, Weihao Kong, Rajat Sen et al.
A Dense Reward View on Aligning Text-to-Image Diffusion with Preference
Shentao Yang, Tianqi Chen, Mingyuan Zhou
A Dual-module Framework for Counterfactual Estimation over Time
Xin Wang, Shengfei Lyu, Lishan Yang et al.
ALERT-Transformer: Bridging Asynchronous and Synchronous Machine Learning for Real-Time Event-based Spatio-Temporal Data
Carmen Martin-Turrero, Maxence Bouvier, Manuel Breitenstein et al.
An Empirical Examination of Balancing Strategy for Counterfactual Estimation on Time Series
Qiang Huang, Chuizheng Meng, Defu Cao et al.
An Improved Finite-time Analysis of Temporal Difference Learning with Deep Neural Networks
Zhifa Ke, Zaiwen Wen, Junyu Zhang
ArCHer: Training Language Model Agents via Hierarchical Multi-Turn RL
Yifei Zhou, Andrea Zanette, Jiayi Pan et al.
Autaptic Synaptic Circuit Enhances Spatio-temporal Predictive Learning of Spiking Neural Networks
Lihao Wang, Zhaofei Yu
Averaging $n$-step Returns Reduces Variance in Reinforcement Learning
Brett Daley, Martha White, Marlos C. Machado
BayOTIDE: Bayesian Online Multivariate Time Series Imputation with Functional Decomposition
Shikai Fang, Qingsong Wen, Yingtao Luo et al.
BeigeMaps: Behavioral Eigenmaps for Reinforcement Learning from Images
Sandesh Adhikary, Anqi Li, Byron Boots
Beyond Point Prediction: Score Matching-based Pseudolikelihood Estimation of Neural Marked Spatio-Temporal Point Process
Zichong Li, Qunzhi Xu, Zhenghao Xu et al.
CaRiNG: Learning Temporal Causal Representation under Non-Invertible Generation Process
Guangyi Chen, Yifan Shen, Zhenhao Chen et al.
CATS: Enhancing Multivariate Time Series Forecasting by Constructing Auxiliary Time Series as Exogenous Variables
Jiecheng Lu, Xu Han, Sun et al.
Causal Customer Churn Analysis with Low-rank Tensor Block Hazard Model
Chenyin Gao, ZHIMING ZHANG, Shu Yang
Causal Representation Learning from Multiple Distributions: A General Setting
Kun Zhang, Shaoan Xie, Ignavier Ng et al.
Causal Representation Learning Made Identifiable by Grouping of Observational Variables
Hiroshi Morioka, Aapo Hyvarinen
CLIF: Complementary Leaky Integrate-and-Fire Neuron for Spiking Neural Networks
Yulong Huang, Xiaopeng LIN, Hongwei Ren et al.
CogBench: a large language model walks into a psychology lab
Julian Coda-Forno, Marcel Binz, Jane Wang et al.
CogDPM: Diffusion Probabilistic Models via Cognitive Predictive Coding
Kaiyuan Chen, Xingzhuo Guo, Yu Zhang et al.
Confronting Reward Overoptimization for Diffusion Models: A Perspective of Inductive and Primacy Biases
Ziyi Zhang, Sen Zhang, Yibing Zhan et al.
Controlling Behavioral Diversity in Multi-Agent Reinforcement Learning
Matteo Bettini, Ryan Kortvelesy, Amanda Prorok
convSeq: Fast and Scalable Method for Detecting Patterns in Spike Data
Roman Koshkin, Tomoki Fukai
DecisionNCE: Embodied Multimodal Representations via Implicit Preference Learning
Jianxiong Li, Jinliang Zheng, Yinan Zheng et al.
Deep Functional Factor Models: Forecasting High-Dimensional Functional Time Series via Bayesian Nonparametric Factorization
Yirui Liu, Xinghao Qiao, Yulong Pei et al.
DIDI: Diffusion-Guided Diversity for Offline Behavioral Generation
Jinxin Liu, Xinghong Guo, Zifeng Zhuang et al.
Diffusion Model-Augmented Behavioral Cloning
Shang-Fu Chen, Hsiang-Chun Wang, Ming-Hao Hsu et al.
Distributional Bellman Operators over Mean Embeddings
Li Kevin Wenliang, Gregoire Deletang, Matthew Aitchison et al.
DoraemonGPT: Toward Understanding Dynamic Scenes with Large Language Models (Exemplified as A Video Agent)
Zongxin Yang, Guikun Chen, Xiaodi Li et al.
Efficient and Effective Time-Series Forecasting with Spiking Neural Networks
Changze Lv, Yansen Wang, Dongqi Han et al.
Efficient Error Certification for Physics-Informed Neural Networks
Francisco Eiras, Adel Bibi, Rudy Bunel et al.
Enhancing Trajectory Prediction through Self-Supervised Waypoint Distortion Prediction
Pranav Singh Chib, Pravendra Singh
Equivariant Graph Neural Operator for Modeling 3D Dynamics
Minkai Xu, Jiaqi Han, Aaron Lou et al.
Evaluation of Trajectory Distribution Predictions with Energy Score
Novin Shahroudi, Mihkel Lepson, Meelis Kull
EVEREST: Efficient Masked Video Autoencoder by Removing Redundant Spatiotemporal Tokens
Sunil Hwang, Jaehong Yoon, Youngwan Lee et al.
EvoluNet: Advancing Dynamic Non-IID Transfer Learning on Graphs
Haohui Wang, Yuzhen Mao, Yujun Yan et al.
EvTexture: Event-driven Texture Enhancement for Video Super-Resolution
Dachun Kai, Jiayao Lu, Yueyi Zhang et al.
Explain Temporal Black-Box Models via Functional Decomposition
Linxiao Yang, Yunze Tong, Xinyue Gu et al.
Fair Off-Policy Learning from Observational Data
Dennis Frauen, Valentyn Melnychuk, Stefan Feuerriegel
FlashST: A Simple and Universal Prompt-Tuning Framework for Traffic Prediction
Zhonghang Li, Lianghao Xia, Yong Xu et al.
Foundation Policies with Hilbert Representations
Seohong Park, Tobias Kreiman, Sergey Levine
From Fourier to Neural ODEs: Flow Matching for Modeling Complex Systems
Xin Li, Jingdong Zhang, Qunxi Zhu et al.
From Generalization Analysis to Optimization Designs for State Space Models
Fusheng Liu, Qianxiao Li
Genie: Generative Interactive Environments
Jake Bruce, Michael Dennis, Ashley Edwards et al.
Graph-based Forecasting with Missing Data through Spatiotemporal Downsampling
Ivan Marisca, Cesare Alippi, Filippo Maria Bianchi
HelmFluid: Learning Helmholtz Dynamics for Interpretable Fluid Prediction
Lanxiang Xing, Haixu Wu, yuezhou ma et al.
Hierarchical State Space Models for Continuous Sequence-to-Sequence Modeling
Raunaq Bhirangi, Chenyu Wang, Venkatesh Pattabiraman et al.