Poster Papers
24,624 papers found • Page 482 of 493
Conference
Uncertainty-aware sign language video retrieval with probability distribution modeling
Xuan Wu, Hongxiang Li, yuanjiang luo et al.
Uncertainty-Aware Source-Free Adaptive Image Super-Resolution with Wavelet Augmentation Transformer
Yuang Ai, Xiaoqiang Zhou, Huaibo Huang et al.
Uncertainty Calibration with Energy Based Instance-wise Scaling in the Wild Dataset
Mijoo Kim, Junseok Kwon
Uncertainty-Driven Spectral Compressive Imaging with Spatial-Frequency Transformer
Lintao Peng, Siyu Xie, Liheng Bian
Uncertainty Estimation by Density Aware Evidential Deep Learning
Taeseong Yoon, Heeyoung Kim
Uncertainty for Active Learning on Graphs
Dominik Fuchsgruber, Tom Wollschläger, Bertrand Charpentier et al.
Uncertainty-Guided Never-Ending Learning to Drive
Lei Lai, Eshed Ohn-Bar, Sanjay Arora et al.
Uncertainty Quantification via Stable Distribution Propagation
Felix Petersen, Aashwin Mishra, Hilde Kuehne et al.
Uncertainty Visualization via Low-Dimensional Posterior Projections
Omer Yair, Tomer Michaeli, Elias Nehme
Unconstrained Stochastic CCA: Unifying Multiview and Self-Supervised Learning
James Chapman, Lennie Wells, Ana Lawry Aguila
Uncovering What Why and How: A Comprehensive Benchmark for Causation Understanding of Video Anomaly
Hang Du, Sicheng Zhang, Binzhu Xie et al.
Understanding Adam Optimizer via Online Learning of Updates: Adam is FTRL in Disguise
Kwangjun Ahn, Zhiyu Zhang, Yunbum Kook et al.
Understanding Addition in Transformers
Philip Quirke, Fazl Barez
Understanding and Diagnosing Deep Reinforcement Learning
Ezgi Korkmaz
Understanding and Improving Source-free Domain Adaptation from a Theoretical Perspective
Yu Mitsuzumi, Akisato Kimura, Hisashi Kashima
Understanding and Mitigating Human-Labelling Errors in Supervised Contrastive Learning
Zijun Long, Lipeng Zhuang, George W Killick et al.
Understanding Catastrophic Forgetting in Language Models via Implicit Inference
Suhas Kotha, Jacob Springer, Aditi Raghunathan
Understanding Certified Training with Interval Bound Propagation
Yuhao Mao, Mark N Müller, Marc Fischer et al.
Understanding Convergence and Generalization in Federated Learning through Feature Learning Theory
Wei Huang, Ye Shi, Zhongyi Cai et al.
Understanding Diffusion Models by Feynman's Path Integral
Yuji Hirono, Akinori Tanaka, Kenji Fukushima
Understanding Domain Generalization: A Noise Robustness Perspective
Rui Qiao, Bryan Kian Hsiang Low
Understanding Expressivity of GNN in Rule Learning
Haiquan Qiu, Yongqi Zhang, Yong Li et al.
Understanding Finetuning for Factual Knowledge Extraction
Gaurav Ghosal, Tatsunori Hashimoto, Aditi Raghunathan
Understanding Forgetting in Continual Learning with Linear Regression
Meng Ding, Kaiyi Ji, Di Wang et al.
Understanding Heterophily for Graph Neural Networks
Junfu Wang, Yuanfang Guo, Liang Yang et al.
Understanding In-Context Learning from Repetitions
Jianhao (Elliott) Yan, Jin Xu, Chiyu Song et al.
Understanding In-Context Learning in Transformers and LLMs by Learning to Learn Discrete Functions
Satwik Bhattamishra, Arkil Patel, Phil Blunsom et al.
Understanding Inter-Concept Relationships in Concept-Based Models
Naveen Raman, Mateo Espinosa Zarlenga, Mateja Jamnik
Understanding MLP-Mixer as a wide and sparse MLP
Tomohiro Hayase, Ryo Karakida
Understanding Multi-compositional learning in Vision and Language models via Category Theory
Sotirios Panagiotis Takis Chytas, Hyunwoo J. Kim, Vikas Singh
Understanding Physical Dynamics with Counterfactual World Modeling
Rahul Mysore Venkatesh, Honglin Chen, Kevin Feigelis et al.
Understanding prompt engineering may not require rethinking generalization
Victor Akinwande, Yiding Jiang, Dylan Sam et al.
Understanding Reasoning Ability of Language Models From the Perspective of Reasoning Paths Aggregation
Xinyi Wang, Alfonso Amayuelas, Kexun Zhang et al.
Understanding Reconstruction Attacks with the Neural Tangent Kernel and Dataset Distillation
Noel Loo, Ramin Hasani, Mathias Lechner et al.
Understanding Retrieval-Augmented Task Adaptation for Vision-Language Models
Yifei Ming, Sharon Li
Understanding Server-Assisted Federated Learning in the Presence of Incomplete Client Participation
Haibo Yang, Peiwen Qiu, Prashant Khanduri et al.
Understanding Stochastic Natural Gradient Variational Inference
Kaiwen Wu, Jacob Gardner
Understanding the Effects of Iterative Prompting on Truthfulness
Satyapriya Krishna, Chirag Agarwal, Himabindu Lakkaraju
Understanding the Effects of RLHF on LLM Generalisation and Diversity
Robert Kirk, Ishita Mediratta, Christoforos Nalmpantis et al.
Understanding the Impact of Introducing Constraints at Inference Time on Generalization Error
Masaaki Nishino, Kengo Nakamura, Norihito Yasuda
Understanding the Learning Dynamics of Alignment with Human Feedback
Shawn Im, Sharon Li
Understanding the robustness difference between stochastic gradient descent and adaptive gradient methods
Avery Ma, Yangchen Pan, Amir-massoud Farahmand
Understanding the Robustness of Multi-modal Contrastive Learning to Distribution Shift
Yihao Xue, Siddharth Joshi, Dang Nguyen et al.
Understanding the Robustness of Randomized Feature Defense Against Query-Based Adversarial Attacks
Hung Quang Nguyen, Yingjie Lao, Tung Pham et al.
Understanding the Training Speedup from Sampling with Approximate Losses
Rudrajit Das, Xi Chen, Bertram Ieong et al.
Understanding Transferable Representation Learning and Zero-shot Transfer in CLIP
Zixiang Chen, Yihe Deng, Yuanzhi Li et al.
Understanding Unimodal Bias in Multimodal Deep Linear Networks
Yedi Zhang, Peter Latham, Andrew Saxe
Understanding when Dynamics-Invariant Data Augmentations Benefit Model-free Reinforcement Learning Updates
Nicholas Corrado, Josiah Hanna
Un-EVIMO: Unsupervised Event-based Independent Motion Segmentation
Ziyun Wang, Jinyuan Guo, Kostas Daniilidis
Unexplored Faces of Robustness and Out-of-Distribution: Covariate Shifts in Environment and Sensor Domains
Eunsu Baek, Keondo Park, Ji-yoon Kim et al.