Papers
11,015 papers found
Approximate Nearest Neighbor Negative Contrastive Learning for Dense Text Retrieval
Lee Xiong, Chenyan Xiong, Ye Li et al.
Are Neural Nets Modular? Inspecting Functional Modularity Through Differentiable Weight Masks
Róbert Csordás, Sjoerd van Steenkiste, Jürgen Schmidhuber
Are Neural Rankers still Outperformed by Gradient Boosted Decision Trees?
Zhen Qin, Le Yan, Honglei Zhuang et al.
Are wider nets better given the same number of parameters?
Anna Golubeva, Guy Gur-Ari, Behnam Neyshabur
ARMOURED: Adversarially Robust MOdels using Unlabeled data by REgularizing Diversity
Kangkang Lu, Cuong Manh Nguyen, Xun Xu et al.
Ask Your Humans: Using Human Instructions to Improve Generalization in Reinforcement Learning
Valerie Chen, Abhinav Gupta, Kenneth Marino
A statistical theory of cold posteriors in deep neural networks
Laurence Aitchison
Async-RED: A Provably Convergent Asynchronous Block Parallel Stochastic Method using Deep Denoising Priors
Yu Sun, Jiaming Liu, Yiran Sun et al.
A teacher-student framework to distill future trajectories
Alexander Neitz, Giambattista Parascandolo, Bernhard Schölkopf
A Temporal Kernel Approach for Deep Learning with Continuous-time Information
Da Xu, Chuanwei Ruan, Evren Korpeoglu et al.
A Trainable Optimal Transport Embedding for Feature Aggregation and its Relationship to Attention
Grégoire Mialon, Dexiong Chen, Alexandre d'Aspremont et al.
Attentional Constellation Nets for Few-Shot Learning
Weijian Xu, yifan xu, Huaijin Wang et al.
Auction Learning as a Two-Player Game
Jad Rahme, Samy Jelassi, S. Matthew Weinberg
Augmenting Physical Models with Deep Networks for Complex Dynamics Forecasting
Yuan Yin, Vincent LE GUEN, Jérémie DONA et al.
A Unified Approach to Interpreting and Boosting Adversarial Transferability
Xin Wang, Jie Ren, Shuyun Lin et al.
A unifying view on implicit bias in training linear neural networks
Chulhee Yun, Shankar Krishnan, Hossein Mobahi
A Universal Representation Transformer Layer for Few-Shot Image Classification
Lu Liu, William L. Hamilton, Guodong Long et al.
AutoLRS: Automatic Learning-Rate Schedule by Bayesian Optimization on the Fly
Yuchen Jin, Tianyi Zhou, Liangyu Zhao et al.
Autoregressive Dynamics Models for Offline Policy Evaluation and Optimization
Michael R Zhang, Thomas Paine, Ofir Nachum et al.
Autoregressive Entity Retrieval
Nicola De Cao, Gautier Izacard, Sebastian Riedel et al.
Auto Seg-Loss: Searching Metric Surrogates for Semantic Segmentation
Hao Li, Chenxin Tao, Xizhou Zhu et al.
Auxiliary Learning by Implicit Differentiation
Aviv Navon, Idan Achituve, Haggai Maron et al.
AUXILIARY TASK UPDATE DECOMPOSITION: THE GOOD, THE BAD AND THE NEUTRAL
Lucio M. Dery, Yann Dauphin, David Grangier
Average-case Acceleration for Bilinear Games and Normal Matrices
Carles Domingo-Enrich, Fabian Pedregosa, Damien Scieur
A Wigner-Eckart Theorem for Group Equivariant Convolution Kernels
Leon Lang, Maurice Weiler