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Poster
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Thu 14:00
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Diffusion Curvature for Estimating Local Curvature in High Dimensional Data
Dhananjay Bhaskar · Kincaid MacDonald · Oluwadamilola Fasina · Dawson Thomas · Bastian Rieck · Ian Adelstein · Smita Krishnaswamy
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Poster
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Wed 9:00
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A Quantitative Geometric Approach to Neural-Network Smoothness
Zi Wang · Gautam Prakriya · Somesh Jha
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Workshop
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On the performance of Direct Loss Minimization for Bayesian Neural Networks
Yadi Wei · Roni Khardon
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Poster
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Thu 14:00
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Is L2 Physics Informed Loss Always Suitable for Training Physics Informed Neural Network?
Chuwei Wang · Shanda Li · Di He · Liwei Wang
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Poster
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Tue 9:00
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Biologically plausible solutions for spiking networks with efficient coding
Veronika Koren · Stefano Panzeri
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Poster
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Tue 9:00
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Gradient flow dynamics of shallow ReLU networks for square loss and orthogonal inputs
Etienne Boursier · Loucas PILLAUD-VIVIEN · Nicolas Flammarion
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Poster
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Tue 14:00
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Understanding Square Loss in Training Overparametrized Neural Network Classifiers
Tianyang Hu · Jun WANG · Wenjia Wang · Zhenguo Li
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Poster
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NeuroSchedule: A Novel Effective GNN-based Scheduling Method for High-level Synthesis
Jun Zeng · Mingyang Kou · Hailong Yao
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Affinity Workshop
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Determination of Neural Network Parameters for Path Loss Prediction in Very High Frequency Wireless Channel
Abigail Jefia · Segun Popoola · Aderemi A. Atayero
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Poster
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IM-Loss: Information Maximization Loss for Spiking Neural Networks
Yufei Guo · Yuanpei Chen · Liwen Zhang · Xiaode Liu · Yinglei Wang · Xuhui Huang · Zhe Ma
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Workshop
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Physically-primed deep-neural-networks for generalized undersampled MRI reconstruction
Nitzan Avidan · Moti Freiman
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Poster
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Thu 9:00
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Pre-Train Your Loss: Easy Bayesian Transfer Learning with Informative Priors
Ravid Shwartz-Ziv · Micah Goldblum · Hossein Souri · Sanyam Kapoor · Chen Zhu · Yann LeCun · Andrew Wilson
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