NEURIPS Poster Papers
4,493 papers found • Page 85 of 90
Uncertainty-Guided Exploration for Efficient AlphaZero Training
Scott Cheng, Meng-Yu Tsai, Ding-Yong Hong et al.
Uncertainty-Informed Meta Pseudo Labeling for Surrogate Modeling with Limited Labeled Data
Xingyu Ren, Pengwei Liu, Pengkai Wang et al.
Uncertainty Quantification for Deep Regression using Contextualised Normalizing Flows
Adriel Sosa Marco, John D. Kirwan, Alexia Toumpa et al.
Uncertainty Quantification for Physics-Informed Neural Networks with Extended Fiducial Inference
Frank Shih, Zhenghao Jiang, Faming Liang
Uncertainty Quantification with the Empirical Neural Tangent Kernel
Joseph Wilson, Chris van der Heide, Liam Hodgkinson et al.
Uncoupled and Convergent Learning in Monotone Games under Bandit Feedback
Jing Dong, Baoxiang Wang, Yaoliang Yu
Uncover Governing Law of Pathology Propagation Mechanism Through A Mean-Field Game
Tingting Dan, Zhihao Fan, Guorong Wu
Uncovering a Universal Abstract Algorithm for Modular Addition in Neural Networks
Gavin McCracken, Gabriela Moisescu-Pareja, Vincent Létourneau et al.
Uncovering the Spectral Bias in Diagonal State Space Models
Ruben Solozabal, Velibor Bojkovic, Hilal AlQuabeh et al.
Understand Before You Generate: Self-Guided Training for Autoregressive Image Generation
Xiaoyu Yue, ZiDong Wang, Yuqing Wang et al.
Understanding Adam Requires Better Rotation Dependent Assumptions
Tianyue Zhang, Lucas Maes, Alan Milligan et al.
Understanding and Enhancing Mask-Based Pretraining towards Universal Representations
Mingze Dong, Leda Wang, Yuval Kluger
Understanding and Enhancing Message Passing on Heterophilic Graphs via Compatibility Matrix
Zhuonan Zheng, Yuanchen Bei, Zhiyao Zhou et al.
Understanding and Improving Adversarial Robustness of Neural Probabilistic Circuits
Weixin Chen, Han Zhao
Understanding and Improving Fast Adversarial Training against $l_0$ Bounded Perturbations
Xuyang Zhong, Yixiao Huang, Chen Liu
Understanding and Rectifying Safety Perception Distortion in VLMs
Xiaohan Zou, Jian Kang, George Kesidis et al.
Understanding Bias Terms in Neural Representations
Weixiang Zhang, Boxi Li, Shuzhao Xie et al.
Understanding challenges to the interpretation of disaggregated evaluations of algorithmic fairness
Stephen Pfohl, Natalie Harris, Chirag Nagpal et al.
Understanding Contrastive Learning via Gaussian Mixture Models
Parikshit Bansal, Ali Kavis, Sujay Sanghavi
Understanding Differential Transformer Unchains Pretrained Self-Attentions
Chaerin Kong, Jiho Jang, Nojun Kwak
Understanding Fairness and Prediction Error through Subspace Decomposition and Influence Analysis
Enze Shi, Pankaj Bhagwat, Zhixian Yang et al.
Understanding Generalization in Physics Informed Models through Affine Variety Dimensions
Takeshi Koshizuka, Issei Sato
Understanding outer learning rates in Local SGD
Ahmed Khaled, Satyen Kale, Arthur Douillard et al.
Understanding protein function with a multimodal retrieval-augmented foundation model
Timothy Truong Jr, Tristan Bepler
Understanding Representation Dynamics of Diffusion Models via Low-Dimensional Modeling
Xiao Li, Zekai Zhang, Xiang Li et al.
Understanding Softmax Attention Layers:\\ Exact Mean-Field Analysis on a Toy Problem
Elvis Dohmatob
Understanding the Evolution of the Neural Tangent Kernel at the Edge of Stability
Kaiqi Jiang, Jeremy Cohen, Yuanzhi Li
Understanding the Gain from Data Filtering in Multimodal Contrastive Learning
Divyansh Pareek, Sewoong Oh, Simon Du
Understanding the Generalization of Stochastic Gradient Adam in Learning Neural Networks
Xuan Tang, Han Zhang, Yuan Cao et al.
Understanding while Exploring: Semantics-driven Active Mapping
Liyan Chen, Huangying Zhan, Hairong Yin et al.
Under the Shadow: Exploiting Opacity Variation for Fine-grained Shadow Detection
Xiaotian Qiao, Ke Xu, Xianglong Yang et al.
Unextractable Protocol Models: Collaborative Training and Inference without Weight Materialization
Alexander Long, Chamin Hewa Koneputugodage, Thalaiyasingam Ajanthan et al.
Unfolding the Black Box of Recurrent Neural Networks for Path Integration
Tianhao Chu, Yuling Wu, Neil Burgess et al.
UniCTokens: Boosting Personalized Understanding and Generation via Unified Concept Tokens
Ruichuan An, Sihan Yang, Renrui Zhang et al.
UniDomain: Pretraining a Unified PDDL Domain from Real-World Demonstrations for Generalizable Robot Task Planning
Haoming Ye, Yunxiao Xiao, Cewu Lu et al.
UniEdit: A Unified Knowledge Editing Benchmark for Large Language Models
Qizhou Chen, Dakan Wang, Taolin Zhang et al.
Unified 2D-3D Discrete Priors for Noise-Robust and Calibration-Free Multiview 3D Human Pose Estimation
Geng Chen, Pengfei Ren, Xufeng Jian et al.
Unified Algorithms for RL with Decision-Estimation Coefficients: PAC, Reward-Free, Preference-Based Learning, and Beyond
Fan Chen, Song Mei, Yu Bai
Unified all-atom molecule generation with neural fields
Matthieu Kirchmeyer, Pedro O. Pinheiro, Emma Willett et al.
Unified Multimodal Chain-of-Thought Reward Model through Reinforcement Fine-Tuning
Yibin Wang, li zhimin, Yuhang Zang et al.
Unified Reinforcement and Imitation Learning for Vision-Language Models
Byung-Kwan Lee, Ryo Hachiuma, Yong Man Ro et al.
Unified Scaling Laws for Compressed Representations
Andrei Panferov, Alexandra Volkova, Ionut-Vlad Modoranu et al.
UniFoil: A Universal Dataset of Airfoils in Transitional and Turbulent Regimes for Subsonic and Transonic Flows
Rohit Kanchi, Benjamin Melanson, Nithin Somasekharan et al.
Uniform Generalization Bounds on Data-Dependent Hypothesis Sets via PAC-Bayesian Theory on Random Sets
Benjamin Dupuis, Paul Viallard, George Deligiannidis et al.
Uniform Wrappers: Bridging Concave to Quadratizable Functions in Online Optimization
Mohammad Pedramfar, Christopher Quinn, Vaneet Aggarwal
Unifying and Enhancing Graph Transformers via a Hierarchical Mask Framework
Yujie Xing, Xiao Wang, Bin Wu et al.
Unifying Appearance Codes and Bilateral Grids for Driving Scene Gaussian Splatting
Nan Wang, Lixing Xiao, Yuantao Chen et al.
Unifying Attention Heads and Task Vectors via Hidden State Geometry in In-Context Learning
Haolin Yang, Hakaze Cho, Yiqiao Zhong et al.
Unifying Reconstruction and Density Estimation via Invertible Contraction Mapping in One-Class Classification
Xiaolei Wang, Tianhong Dai, Huihui Bai et al.
Unifying Re-Identification, Attribute Inference, and Data Reconstruction Risks in Differential Privacy
Bogdan Kulynych, Juan Gomez, Georgios Kaissis et al.