Poster

Thu 14:00

Diffusion Curvature for Estimating Local Curvature in High Dimensional Data
Dhananjay Bhaskar · Kincaid MacDonald · Oluwadamilola Fasina · Dawson Thomas · Bastian Rieck · Ian Adelstein · Smita Krishnaswamy

Poster

Wed 9:00

A Quantitative Geometric Approach to Neural-Network Smoothness
Zi Wang · Gautam Prakriya · Somesh Jha

Workshop

On the performance of Direct Loss Minimization for Bayesian Neural Networks
Yadi Wei · Roni Khardon

Poster

Thu 14:00

Is $L^2$ Physics Informed Loss Always Suitable for Training Physics Informed Neural Network?
Chuwei Wang · Shanda Li · Di He · Liwei Wang

Poster

Tue 9:00

Gradient flow dynamics of shallow ReLU networks for square loss and orthogonal inputs
Etienne Boursier · Loucas PILLAUD-VIVIEN · Nicolas Flammarion

Poster

Tue 9:00

Biologically plausible solutions for spiking networks with efficient coding
Veronika Koren · Stefano Panzeri

Poster

NeuroSchedule: A Novel Effective GNN-based Scheduling Method for High-level Synthesis
Jun Zeng · Mingyang Kou · Hailong Yao

Affinity Workshop

Determination of Neural Network Parameters for Path Loss Prediction in Very High Frequency Wireless Channel
Abigail Jefia · Segun Popoola · Aderemi A. Atayero

Poster

Tue 14:00

Understanding Square Loss in Training Overparametrized Neural Network Classifiers
Tianyang Hu · Jun WANG · Wenjia Wang · Zhenguo Li

Poster

IM-Loss: Information Maximization Loss for Spiking Neural Networks
Yufei Guo · Yuanpei Chen · Liwen Zhang · Xiaode Liu · Yinglei Wang · Xuhui Huang · Zhe Ma

Workshop

Physically-primed deep-neural-networks for generalized undersampled MRI reconstruction
Nitzan Avidan · Moti Freiman

Poster

Thu 9:00

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