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ORCIDPreregister 2020: Virtual Event
- Luca Bertinetto, João F. Henriques, Samuel Albanie, Michela Paganini, Gül Varol:
NeurIPS 2020 Workshop on Pre-registration in Machine Learning, 11 December 2020, Virtual Event. Proceedings of Machine Learning Research 148, PMLR 2020 - Luca Bertinetto, João F. Henriques, Samuel Albanie, Michela Paganini, Gül Varol:
Preface. i - Kexue Fu, Xiaoyuan Luo, Manning Wang:
Point Cloud Overlapping Region Co-Segmentation Network. 1-13 - Akshay L. Chandra, Sai Vikas Desai, Chaitanya Devaguptapu, Vineeth N. Balasubramanian:
On Initial Pools for Deep Active Learning. 14-32 - Liu Yuezhang, Bo Li, Qifeng Chen:
Evaluating Adversarial Robustness in Simulated Cerebellum. 33-50 - Xuehao Gao, Yang Yang, Shaoyi Du:
Contrastive Self-Supervised Learning for Skeleton Action Recognition. 51-61 - Ayush Jaiswal, Simranjit Singh, Yue Wu, Pradeep Natarajan, Premkumar Natarajan:
Keypoints-aware Object Detection. 62-72 - Cade Gordon, Natalie Parde:
Latent Neural Differential Equations for Video Generation. 73-86 - Eimear O' Sullivan, Stefanos Zafeiriou:
PCA Retargeting: Encoding Linear Shape Models as Convolutional Mesh Autoencoders. 87-99 - Rasmus Berg Palm, Elias Najarro, Sebastian Risi:
Testing the Genomic Bottleneck Hypothesis in Hebbian Meta-Learning. 100-110 - Rodrigo Alves, Antoine Ledent, Renato Assunção, Marius Kloft:
An Empirical Study of the Discreteness Prior in Low-Rank Matrix Completion. 111-125 - Elena Burceanu:
SFTrack++: A Fast Learnable Spectral Segmentation Approach for Space-Time Consistent Tracking. 126-138 - Rishika Bhagwatkar, Khurshed Fitter, Saketh Bachu, Akshay R. Kulkarni, Shital S. Chiddarwar:
Paying Attention to Video Generation. 139-154 - Arnout Devos, Yatin Dandi:
Model-Agnostic Learning to Meta-Learn. 155-175 - Carianne Martinez, David A. Najera-Flores, Adam R. Brink, D. Dane Quinn, Eleni N. Chatzi, Stephanie Forrest:
Confronting Domain Shift in Trained Neural Networks. 176-192 - João Monteiro, Xavier Gibert Serra, Jianqiao Feng, Vincent Dumoulin, Dar-Shyang Lee:
Domain Conditional Predictors for Domain Adaptation. 193-220 - Tanner A. Bohn, Xinyu Yun, Charles X. Ling:
Towards a Unified Lifelong Learning Framework. 221-235 - Hamid Eghbal-zadeh, Florian Henkel, Gerhard Widmer:
Context-Adaptive Reinforcement Learning using Unsupervised Learning of Context Variables. 236-254 - Aneesh Dahiya, Adrian Spurr, Otmar Hilliges:
Exploring self-supervised learning techniques for hand pose estimation. 255-271 - Miles D. Cranmer, Peter Melchior, Brian Nord:
Unsupervised Resource Allocation with Graph Neural Networks. 272-284 - Owen Lockwood, Mei Si:
Playing Atari with Hybrid Quantum-Classical Reinforcement Learning. 285-301 - Ajinkya Mulay, Gaspard Baye, Rakshit Naidu, Santiago González-Toral, Vineeth S, Tushar Semwal, Ayush Manish Agrawal:
FedPerf: A Practitioners' Guide to Performance of Federated Learning Algorithms. 302-324 - Philipp Benz, Chaoning Zhang, Adil Karjauv, In So Kweon:
Robustness May Be at Odds with Fairness: An Empirical Study on Class-wise Accuracy. 325-342 - Ruizhe Li, Xutan Peng, Chenghua Lin, Wenge Rong, Zhigang Chen:
On the Low-density Latent Regions of VAE-based Language Models. 343-357 - Meenakshi Sarkar, Debasish Ghose, Aniruddha Bala:
Decomposing camera and object motion for an improved video sequence prediction. 358-374
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