ICLR 2024 Papers
2,297 papers found • Page 2 of 46
ADDP: Learning General Representations for Image Recognition and Generation with Alternating Denoising Diffusion Process
Changyao Tian, Chenxin Tao, Jifeng Dai et al.
Addressing Loss of Plasticity and Catastrophic Forgetting in Continual Learning
Mohamed Elsayed, A. Rupam Mahmood
Addressing Signal Delay in Deep Reinforcement Learning
Wei Wang, Dongqi Han, Xufang Luo et al.
A differentiable brain simulator bridging brain simulation and brain-inspired computing
Chaoming Wang, Tianqiu Zhang, Sichao He et al.
A Differentially Private Clustering Algorithm for Well-Clustered Graphs
Weiqiang He, Hendrik Fichtenberger, Pan Peng
A Discretization Framework for Robust Contextual Stochastic Optimization
Rares Cristian, Georgia Perakis
AdjointDPM: Adjoint Sensitivity Method for Gradient Backpropagation of Diffusion Probabilistic Models
Jiachun Pan, Jiachun Pan, Jun Hao Liew et al.
ADOPD: A Large-Scale Document Page Decomposition Dataset
Jiuxiang Gu, Xiangxi Shi, Jason Kuen et al.
Advancing Pose-Guided Image Synthesis with Progressive Conditional Diffusion Models
Fei Shen, Hu Ye, Jun Zhang et al.
Advancing the Lower Bounds: an Accelerated, Stochastic, Second-order Method with Optimal Adaptation to Inexactness
Artem Agafonov, Dmitry Kamzolov, Alexander Gasnikov et al.
Adversarial Adaptive Sampling: Unify PINN and Optimal Transport for the Approximation of PDEs
Kejun Tang, Jiayu Zhai, Xiaoliang Wan et al.
Adversarial Attacks on Fairness of Graph Neural Networks
Binchi Zhang, Yushun Dong, Chen Chen et al.
Adversarial AutoMixup
Huafeng Qin, Xin Jin, Yun Jiang et al.
Adversarial Causal Bayesian Optimization
Scott Sussex, Pier Giuseppe Sessa, Anastasia Makarova et al.
Adversarial Feature Map Pruning for Backdoor
Dong HUANG, Qingwen Bu
Adversarial Imitation Learning via Boosting
Jonathan Chang, Dhruv Sreenivas, Yingbing Huang et al.
Adversarial Supervision Makes Layout-to-Image Diffusion Models Thrive
Yumeng Li, Margret Keuper, Dan Zhang et al.
Adversarial Training on Purification (AToP): Advancing Both Robustness and Generalization
Guang Lin, Chao Li, Jianhai Zhang et al.
Adversarial Training Should Be Cast as a Non-Zero-Sum Game
Alex Robey, Fabian Latorre, George Pappas et al.
A Dynamical View of the Question of Why
Mehdi Fatemi, Sindhu Chatralinganadoddi Mariyappa Gowda
A Fast and Provable Algorithm for Sparse Phase Retrieval
Jian-Feng Cai, Yu Long, Ruixue WEN et al.
AffineQuant: Affine Transformation Quantization for Large Language Models
Yuexiao Ma, Huixia Li, Xiawu Zheng et al.
A Flexible Generative Model for Heterogeneous Tabular EHR with Missing Modality
Huan He, Yijie Hao, Yuanzhe Xi et al.
A Foundation Model for Error Correction Codes
Yoni Choukroun, Lior Wolf
A Framework and Benchmark for Deep Batch Active Learning for Regression
David Holzmüller, Viktor Zaverkin, Johannes Kästner et al.
A Framework for Inference Inspired by Human Memory Mechanisms
Xiangyu Zeng, Jie Lin, Piao Hu et al.
A General Framework for User-Guided Bayesian Optimization
Carl Hvarfner, Frank Hutter, Luigi Nardi
A Generalist Agent
Jackie Kay, Sergio Gómez Colmenarejo, Mahyar Bordbar et al.
AgentBench: Evaluating LLMs as Agents
Xiao Liu, Hao Yu, Hanchen Zhang et al.
AgentVerse: Facilitating Multi-Agent Collaboration and Exploring Emergent Behaviors
Weize Chen, Yusheng Su, Jingwei Zuo et al.
AGILE3D: Attention Guided Interactive Multi-object 3D Segmentation
Yuanwen Yue, Sabarinath Mahadevan, Jonas Schult et al.
A Good Learner can Teach Better: Teacher-Student Collaborative Knowledge Distillation
Ayan Sengupta, Shantanu Dixit, Md Shad Akhtar et al.
A Graph is Worth 1-bit Spikes: When Graph Contrastive Learning Meets Spiking Neural Networks
Jintang Li, Huizhe Zhang, Ruofan Wu et al.
A Hard-to-Beat Baseline for Training-free CLIP-based Adaptation
Zhengbo Wang, Jian Liang, Lijun Sheng et al.
A Hierarchical Bayesian Model for Few-Shot Meta Learning
Minyoung Kim, Timothy Hospedales
AirPhyNet: Harnessing Physics-Guided Neural Networks for Air Quality Prediction
Kethmi Hirushini Hettige, Jiahao Ji, Shili Xiang et al.
ALAM: Averaged Low-Precision Activation for Memory-Efficient Training of Transformer Models
Sunghyeon Woo, SunWoo Lee, Dongsuk Jeon
Algorithms for Caching and MTS with reduced number of predictions
Karim Ahmed Abdel Sadek, Marek Elias
Alice Benchmarks: Connecting Real World Re-Identification with the Synthetic
Xiaoxiao Sun, Yue Yao, Shengjin Wang et al.
A Lie Group Approach to Riemannian Batch Normalization
Ziheng Chen, Yue Song, Yunmei Liu et al.
A Lightweight Method for Tackling Unknown Participation Statistics in Federated Averaging
Shiqiang Wang, Mingyue Ji
AlignDiff: Aligning Diverse Human Preferences via Behavior-Customisable Diffusion Model
Zibin Dong, Yifu Yuan, Jianye HAO et al.
Aligning Relational Learning with Lipschitz Fairness
Yaning Jia, Chunhui Zhang, Soroush Vosoughi
Align With Purpose: Optimize Desired Properties in CTC Models with a General Plug-and-Play Framework
Eliya Segev, Maya Alroy, Ronen Katsir et al.
A Linear Algebraic Framework for Counterfactual Generation
Jong-Hoon Ahn, Akshay Vashist
Alleviating Exposure Bias in Diffusion Models through Sampling with Shifted Time Steps
Mingxiao Li, Tingyu Qu, Ruicong Yao et al.
AlpaGasus: Training a Better Alpaca with Fewer Data
Lichang Chen, Shiyang Li, Jun Yan et al.
Alt-Text with Context: Improving Accessibility for Images on Twitter
Nikita Srivatsan, Sofia Samaniego, Omar Florez et al.
AMAGO: Scalable In-Context Reinforcement Learning for Adaptive Agents
Jake Grigsby, Jim Fan, Yuke Zhu
Amortized Network Intervention to Steer the Excitatory Point Processes
Zitao Song, Wendi Ren, Shuang Li