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Editors: Jessica Zosa Forde, Francisco Ruiz, Melanie F. Pradier, Aaron Schein
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Uses and Abuses of the Cross-Entropy Loss: Case Studies in Modern Deep Learning
; Proceedings on "I Can't Believe It's Not Better!" at NeurIPS Workshops, PMLR 137:1-10
Further Analysis of Outlier Detection with Deep Generative Models
Ziyu Wang, Bin Dai, David Wipf, Jun Zhu; Proceedings on "I Can't Believe It's Not Better!" at NeurIPS Workshops, PMLR 137:11-20
A case for new neural network smoothness constraints
Mihaela Rosca, Theophane Weber, Arthur Gretton, Shakir Mohamed; Proceedings on "I Can't Believe It's Not Better!" at NeurIPS Workshops, PMLR 137:21-32
The Curious Case of Stacking Boosted Relational Dependency Networks
Siwen Yan, Devendra Singh Dhami, Sriraam Natarajan; Proceedings on "I Can't Believe It's Not Better!" at NeurIPS Workshops, PMLR 137:33-42
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Inferential Induction: A Novel Framework for Bayesian Reinforcement Learning
Emilio Jorge, Hannes Eriksson, Christos Dimitrakakis, Debabrota Basu, Divya Grover; Proceedings on "I Can't Believe It's Not Better!" at NeurIPS Workshops, PMLR 137:43-52
Problems using deep generative models for probabilistic audio source separation
Maurice Frank, Maximilian Ilse; Proceedings on "I Can't Believe It's Not Better!" at NeurIPS Workshops, PMLR 137:53-59
Self-Tuning Stochastic Optimization with Curvature-Aware Gradient Filtering
Ricky T. Q. Chen, Dami Choi, Lukas Balles, David Duvenaud, Philipp Hennig; Proceedings on "I Can't Believe It's Not Better!" at NeurIPS Workshops, PMLR 137:60-69
Less can be more in contrastive learning
Jovana Mitrovic, Brian McWilliams, Melanie Rey; Proceedings on "I Can't Believe It's Not Better!" at NeurIPS Workshops, PMLR 137:70-75
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Decision-Aware Model Learning for Actor-Critic Methods: When Theory Does Not Meet Practice
Ângelo G. Lovatto, Thiago P. Bueno, Denis D. Mauá, Leliane N. Barros; Proceedings on "I Can't Believe It's Not Better!" at NeurIPS Workshops, PMLR 137:76-86
Understanding Generalization Through Visualizations
W. Ronny Huang, Zeyad Emam, Micah Goldblum, Liam Fowl, J. K. Terry, Furong Huang, Tom Goldstein; Proceedings on "I Can't Believe It's Not Better!" at NeurIPS Workshops, PMLR 137:87-97
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A Worrying Analysis of Probabilistic Time-series Models for Sales Forecasting
Seungjae Jung, Kyung-Min Kim, Hanock Kwak, Young-Jin Park; Proceedings on "I Can't Believe It's Not Better!" at NeurIPS Workshops, PMLR 137:98-105
Pitfalls in Machine Learning Research: Reexamining the Development Cycle
Stella Biderman, Walter J. Scheirer; Proceedings on "I Can't Believe It's Not Better!" at NeurIPS Workshops, PMLR 137:106-117
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End-to-End Differentiable GANs for Text Generation
Sachin Kumar, Yulia Tsvetkov; Proceedings on "I Can't Believe It's Not Better!" at NeurIPS Workshops, PMLR 137:118-128
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A study of quality and diversity in K+1 GANs
Ilya Kavalerov, Wojciech Czaja, Rama Chellappa; Proceedings on "I Can't Believe It's Not Better!" at NeurIPS Workshops, PMLR 137:129-135
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Graph Conditional Variational Models: Too Complex for Multiagent Trajectories?
Yannick Rudolph, Ulf Brefeld, Uwe Dick; Proceedings on "I Can't Believe It's Not Better!" at NeurIPS Workshops, PMLR 137:136-147
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Oversampling Tabular Data with Deep Generative Models: Is it worth the effort?
Ramiro D. Camino, Radu State, Christian A. Hammerschmidt; Proceedings on "I Can't Believe It's Not Better!" at NeurIPS Workshops, PMLR 137:148-157
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