ICLR 2024 Poster Papers
1,776 papers found • Page 1 of 36
$\alpha$TC-VAE: On the relationship between Disentanglement and Diversity
Cristian Meo, Louis Mahon, Anirudh Goyal et al.
$\infty$-Diff: Infinite Resolution Diffusion with Subsampled Mollified States
Sam Bond-Taylor, Chris G Willcocks
$\mathbb{D}^2$ Pruning: Message Passing for Balancing Diversity & Difficulty in Data Pruning
Adyasha Maharana, Prateek Yadav, Mohit Bansal
$\pi$2vec: Policy Representation with Successor Features
Gianluca Scarpellini, Ksenia Konyushkova, Claudio Fantacci et al.
$t^3$-Variational Autoencoder: Learning Heavy-tailed Data with Student's t and Power Divergence
Juno Kim, Jaehyuk Kwon, Mincheol Cho et al.
3D-Aware Hypothesis & Verification for Generalizable Relative Object Pose Estimation
Chen Zhao, Tong Zhang, Mathieu Salzmann
3D Feature Prediction for Masked-AutoEncoder-Based Point Cloud Pretraining
Siming Yan, Yuqi Yang, Yu-Xiao Guo et al.
3D Reconstruction with Generalizable Neural Fields using Scene Priors
Yang Fu, Shalini De Mello, Xueting Li et al.
A 2-Dimensional State Space Layer for Spatial Inductive Bias
Ethan Baron, Itamar Zimerman, Lior Wolf
A Benchmark Study on Calibration
Linwei Tao, Younan Zhu, Haolan Guo et al.
A Black-box Approach for Non-stationary Multi-agent Reinforcement Learning
Haozhe Jiang, Qiwen Cui, Zhihan Xiong et al.
A Branching Decoder for Set Generation
Zixian Huang, Gengyang Xiao, Yu Gu et al.
Abstractors and relational cross-attention: An inductive bias for explicit relational reasoning in Transformers
Awni Altabaa, Taylor Webb, Jonathan Cohen et al.
Accelerated Convergence of Stochastic Heavy Ball Method under Anisotropic Gradient Noise
Rui Pan, Yuxing Liu, Xiaoyu Wang et al.
Accelerated Sampling with Stacked Restricted Boltzmann Machines
Jorge Fernandez-de-Cossio-Diaz, Clément Roussel, Simona Cocco et al.
Accelerating Distributed Stochastic Optimization via Self-Repellent Random Walks
Jie Hu, Vishwaraj Doshi, Do Young Eun
Accelerating Sinkhorn algorithm with sparse Newton iterations
Xun Tang, Michael Shavlovsky, Holakou Rahmanian et al.
Accurate and Scalable Estimation of Epistemic Uncertainty for Graph Neural Networks
Puja Trivedi, Mark Heimann, Rushil Anirudh et al.
Accurate Forgetting for Heterogeneous Federated Continual Learning
Abudukelimu Wuerkaixi, Sen Cui, Jingfeng Zhang et al.
Accurate Retraining-free Pruning for Pretrained Encoder-based Language Models
Seungcheol Park, Hojun Choi, U Kang
A Characterization Theorem for Equivariant Networks with Point-wise Activations
Marco Pacini, Xiaowen Dong, Bruno Lepri et al.
Achieving Fairness in Multi-Agent MDP Using Reinforcement Learning
Peizhong Ju, Arnob Ghosh, Ness Shroff
Achieving Human Parity in Content-Grounded Datasets Generation
Asaf Yehudai, Boaz Carmeli, Yosi Mass et al.
Achieving Sample and Computational Efficient Reinforcement Learning by Action Space Reduction via Grouping
Yining Li, Peizhong Ju, Ness Shroff
Achieving the Pareto Frontier of Regret Minimization and Best Arm Identification in Multi-Armed Bandits
Wang Chi Cheung, Vincent Tan, Zixin Zhong
ACRF: Compressing Explicit Neural Radiance Fields via Attribute Compression
Guangchi Fang, Qingyong Hu, Longguang Wang et al.
Active Retrosynthetic Planning Aware of Route Quality
Luotian Yuan, Yemin Yu, Ying Wei et al.
Active Test-Time Adaptation: Theoretical Analyses and An Algorithm
Shurui Gui, Xiner Li, Shuiwang Ji
AdaMerging: Adaptive Model Merging for Multi-Task Learning
Enneng Yang, Zhenyi Wang, Li Shen et al.
Adapting and Evaluating Influence-Estimation Methods for Gradient-Boosted Decision Trees
Jonathan Brophy, Zayd Hammoudeh, Daniel Lowd
Adapting Large Language Models via Reading Comprehension
Daixuan Cheng, Shaohan Huang, Furu Wei
Adapting to Distribution Shift by Visual Domain Prompt Generation
Zhixiang Chi, Li Gu, Tao Zhong et al.
Adaptive deep spiking neural network with global-local learning via balanced excitatory and inhibitory mechanism
Tingting Jiang, Qi Xu, Xuming Ran et al.
Adaptive Federated Learning with Auto-Tuned Clients
Junhyung Lyle Kim, Mohammad Taha Toghani, Cesar Uribe et al.
Adaptive Instrument Design for Indirect Experiments
Yash Chandak, Shiv Shankar, Vasilis Syrgkanis et al.
Adaptive Regret for Bandits Made Possible: Two Queries Suffice
Zhou Lu, Qiuyi (Richard) Zhang, Xinyi Chen et al.
Adaptive Regularization of Representation Rank as an Implicit Constraint of Bellman Equation
Qiang HE, Tianyi Zhou, Meng Fang et al.
Adaptive Retrieval and Scalable Indexing for k-NN Search with Cross-Encoders
Nishant Yadav, Nicholas Monath, Manzil Zaheer et al.
Adaptive Self-training Framework for Fine-grained Scene Graph Generation
Kibum Kim, Kanghoon Yoon, Yeonjun In et al.
Adaptive Sharpness-Aware Pruning for Robust Sparse Networks
Anna Bair, Hongxu Yin, Maying Shen et al.
Adaptive Stochastic Gradient Algorithm for Black-box Multi-Objective Learning
Feiyang YE, YUEMING LYU, Xuehao Wang et al.
Adaptive Window Pruning for Efficient Local Motion Deblurring
Haoying Li, Jixin Zhao, Shangchen Zhou et al.
A Data-Driven Measure of Relative Uncertainty for Misclassification Detection
Eduardo Dadalto Câmara Gomes, Marco Romanelli, Georg Pichler et al.
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
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.