Papers
11,951 papers found
CompOFA – Compound Once-For-All Networks for Faster Multi-Platform Deployment
Manas Sahni, Shreya Varshini, Alind Khare et al.
Computational Separation Between Convolutional and Fully-Connected Networks
eran malach, Shai Shalev-Shwartz
Concept Learners for Few-Shot Learning
Kaidi Cao, Maria Brbic, Jure Leskovec
Conditional Generative Modeling via Learning the Latent Space
Sameera Ramasinghe, Kanchana Nisal Ranasinghe, Salman Khan et al.
Conditionally Adaptive Multi-Task Learning: Improving Transfer Learning in NLP Using Fewer Parameters & Less Data
Jonathan Pilault, Amine El hattami, Christopher Pal
Conditional Negative Sampling for Contrastive Learning of Visual Representations
Mike Wu, Milan Mosse, Chengxu Zhuang et al.
Conformation-Guided Molecular Representation with Hamiltonian Neural Networks
Ziyao Li, Shuwen Yang, Guojie Song et al.
Conservative Safety Critics for Exploration
Homanga Bharadhwaj, Aviral Kumar, Nicholas Rhinehart et al.
Contextual Dropout: An Efficient Sample-Dependent Dropout Module
XINJIE FAN, Shujian Zhang, Korawat Tanwisuth et al.
Contextual Transformation Networks for Online Continual Learning
Quang Pham, Chenghao Liu, Doyen Sahoo et al.
Continual learning in recurrent neural networks
Benjamin Ehret, Christian Henning, Maria Cervera et al.
Continuous Wasserstein-2 Barycenter Estimation without Minimax Optimization
Alexander Korotin, Lingxiao Li, Justin Solomon et al.
Contrastive Behavioral Similarity Embeddings for Generalization in Reinforcement Learning
Rishabh Agarwal, Marlos C. Machado, Pablo Samuel Castro et al.
Contrastive Divergence Learning is a Time Reversal Adversarial Game
Omer Yair, Tomer Michaeli
Contrastive Explanations for Reinforcement Learning via Embedded Self Predictions
Zhengxian Lin, Kin-Ho Lam, Alan Fern
Contrastive Learning with Adversarial Perturbations for Conditional Text Generation
Seanie Lee, Dong Bok Lee, Sung Ju Hwang
Contrastive Learning with Hard Negative Samples
Joshua David Robinson, Ching-Yao Chuang, Suvrit Sra et al.
Contrastively Disentangled Sequential Variational Autoencoder
Junwen Bai, Weiran Wang, Carla P. Gomes
Contrastive Syn-to-Real Generalization
Wuyang Chen, Zhiding Yu, Shalini De Mello et al.
Control-Aware Representations for Model-based Reinforcement Learning
Brandon Cui, Yinlam Chow, Mohammad Ghavamzadeh
Convergence Guarantees for Gaussian Process Means With Misspecified Likelihoods and Smoothness
George Wynne, François-Xavier Briol, Mark Girolami
Convergence of Gaussian-smoothed optimal transport distance with sub-gamma distributions and dependent samples
Yixing Zhang, Xiuyuan Cheng, Galen Reeves
Convex Potential Flows: Universal Probability Distributions with Optimal Transport and Convex Optimization
Chin-Wei Huang, Ricky T. Q. Chen, Christos Tsirigotis et al.
Convex Regularization behind Neural Reconstruction
Arda Sahiner, Morteza Mardani, Batu Ozturkler et al.