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Workshop
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Learning to Compress: Local Rank and Information Compression in Deep Neural Networks
Niket Patel · Ravid Shwartz-Ziv
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Workshop
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IgBlend: Unifying 3D Structure and Sequence for Antibody LLMs
Cédric Malherbe · Talip Ucar
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Poster
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Fri 11:00
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Provable Editing of Deep Neural Networks using Parametric Linear Relaxation
Zhe Tao · Aditya V Thakur
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Oral Session
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Fri 15:30
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Oral Session 6D: Deep Learning Architecture, Infrastructure
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Poster
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Wed 11:00
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Constructing Semantics-Aware Adversarial Examples with a Probabilistic Perspective
Andi Zhang · Mingtian Zhang · Damon Wischik
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Poster
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Thu 16:30
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TabularBench: Benchmarking Adversarial Robustness for Tabular Deep Learning in Real-world Use-cases
Thibault Simonetto · Salah GHAMIZI · Maxime Cordy
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Poster
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Thu 11:00
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Learning and Transferring Sparse Contextual Bigrams with Linear Transformers
Yunwei Ren · Zixuan Wang · Jason Lee
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Session
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Thu 16:30
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Neural Tides: Oceanic Neural Granular Synthesizer
Ryan Millett · Seyeon Park · Sabina Hyoju Ahn
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Workshop
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Sat 12:00
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Hessian-Free Laplace in Bayesian Deep Learning
James McInerney · Nathan Kallus
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Poster
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Thu 16:30
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FSP-Laplace: Function-Space Priors for the Laplace Approximation in Bayesian Deep Learning
Tristan Cinquin · Marvin Pförtner · Vincent Fortuin · Philipp Hennig · Robert Bamler
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Poster
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Fri 16:30
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Nuclear Norm Regularization for Deep Learning
Christopher Scarvelis · Justin Solomon
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Workshop
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A theoretical study of the (L0,L1)-smoothness condition in deep learning
Y Cooper
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