Papers
Emergent Correspondence from Image Diffusion
Luming Tang, Menglin Jia, Qianqian Wang et al.
EMMA-X: An EM-like Multilingual Pre-training Algorithm for Cross-lingual Representation Learning
Ping Guo, Xiangpeng Wei, Yue Hu et al.
Empowering Collaborative Filtering with Principled Adversarial Contrastive Loss
An Zhang, Leheng Sheng, Zhibo Cai et al.
Empowering Convolutional Neural Nets with MetaSin Activation
Farnood Salehi, Tunç Aydin, André Gaillard et al.
Encoding Human Behavior in Information Design through Deep Learning
Guanghui Yu, Wei Tang, Saumik Narayanan et al.
Encoding Time-Series Explanations through Self-Supervised Model Behavior Consistency
Owen Queen, Tom Hartvigsen, Teddy Koker et al.
End-To-End Latent Variational Diffusion Models for Inverse Problems in High Energy Physics
Alexander Shmakov, Kevin Greif, Michael Fenton et al.
End-to-End Meta-Bayesian Optimisation with Transformer Neural Processes
Alexandre Maraval, Matthieu Zimmer, Antoine Grosnit et al.
Energy-Based Cross Attention for Bayesian Context Update in Text-to-Image Diffusion Models
Geon Yeong Park, Jeongsol Kim, Beomsu Kim et al.
Energy-based learning algorithms for analog computing: a comparative study
Benjamin Scellier, Maxence Ernoult, Jack Kendall et al.
Energy-Based Models for Anomaly Detection: A Manifold Diffusion Recovery Approach
Sangwoong Yoon, Young-Uk Jin, Yung-Kyun Noh et al.
Energy-Based Sliced Wasserstein Distance
Khai Nguyen, Nhat Ho
Energy Discrepancies: A Score-Independent Loss for Energy-Based Models
Tobias Schröder, Zijing Ou, Jen Lim et al.
Energy-Efficient Scheduling with Predictions
Eric Balkanski, Noemie Perivier, Clifford Stein et al.
Energy Guided Diffusion for Generating Neurally Exciting Images
Pawel Pierzchlewicz, Konstantin Willeke, Arne Nix et al.
Energy Transformer
Benjamin Hoover, Yuchen Liang, Bao Pham et al.
Enhancing Adaptive History Reserving by Spiking Convolutional Block Attention Module in Recurrent Neural Networks
Qi Xu, Yuyuan Gao, Jiangrong Shen et al.
Enhancing Adversarial Contrastive Learning via Adversarial Invariant Regularization
Xilie Xu, Jingfeng ZHANG, Feng Liu et al.
Enhancing Adversarial Robustness via Score-Based Optimization
Boya Zhang, Weijian Luo, Zhihua Zhang
Enhancing CLIP with CLIP: Exploring Pseudolabeling for Limited-Label Prompt Tuning
Cristina Menghini, Andrew Delworth, Stephen Bach
Enhancing Knowledge Transfer for Task Incremental Learning with Data-free Subnetwork
Qiang Gao, Xiaojun Shan, Yuchen Zhang et al.
Enhancing Minority Classes by Mixing: An Adaptative Optimal Transport Approach for Long-tailed Classification
Jintong Gao, He Zhao, Zhuo Li et al.
Enhancing Motion Deblurring in High-Speed Scenes with Spike Streams
Shiyan Chen, Jiyuan Zhang, Yajing Zheng et al.
Enhancing Robot Program Synthesis Through Environmental Context
Tianyi Chen, Qidi Wang, Zhen Dong et al.
Enhancing Sharpness-Aware Optimization Through Variance Suppression
Bingcong Li, Georgios Giannakis