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Workshop
Auto-regressive WaveNet Variational Autoencoders for Alignment-free Generative Protein Design and Fitness Prediction
Niksa Praljak · Andrew Ferguson
Poster
Mon 18:30 Hot-Refresh Model Upgrades with Regression-Free Compatible Training in Image Retrieval
Binjie Zhang · Yixiao Ge · Yantao Shen · Yu Li · Chun Yuan · XUYUAN XU · Yexin Wang · Ying Shan
Poster
Tue 10:30 Label Encoding for Regression Networks
Deval Shah · Zi Yu Xue · Tor Aamodt
Poster
Thu 10:30 Practical Integration via Separable Bijective Networks
Christopher Bender · Patrick Emmanuel · Michael Reiter · Junier Oliva
Poster
Wed 18:30 Symbolic Learning to Optimize: Towards Interpretability and Scalability
Wenqing Zheng · Tianlong Chen · Ting-Kuei Hu · Zhangyang Wang
Poster
Tue 10:30 A NON-PARAMETRIC REGRESSION VIEWPOINT : GENERALIZATION OF OVERPARAMETRIZED DEEP RELU NETWORK UNDER NOISY OBSERVATIONS
Namjoon Suh · Hyunouk Ko · Xiaoming Huo
Poster
Thu 10:30 Learning Curves for Gaussian Process Regression with Power-Law Priors and Targets
Hui Jin · Pradeep Kumar Banerjee · Guido Montufar
Poster
Mon 10:30 Anisotropic Random Feature Regression in High Dimensions
Gabriel Mel · Jeffrey Pennington
Workshop
Sparsifying the Update Step in Graph Neural Networks
Johannes Lutzeyer · Changmin Wu · Michalis Vazirgiannis
Workshop
Regression Transformer: Concurrent Conditional Generation and Regression by Blending Numerical and Textual Tokens
Jannis Born · Matteo Manica
Poster
Thu 18:30 On the benefits of maximum likelihood estimation for Regression and Forecasting
Pranjal Awasthi · Abhimanyu Das · Rajat Sen · Ananda Suresh
Spotlight
Thu 2:30 D-CODE: Discovering Closed-form ODEs from Observed Trajectories
Zhaozhi Qian · Krzysztof Kacprzyk · Mihaela van der Schaar