Deep Probability Estimation

no code implementations • 21 Nov 2021 • Sheng Liu, Aakash Kaku, Weicheng Zhu, Matan Leibovich, Sreyas Mohan, Boyang Yu, Haoxiang Huang, Laure Zanna, Narges Razavian, Jonathan Niles-Weed, Carlos Fernandez-Granda

Reliable probability estimation is of crucial importance in many real-world applications where there is inherent (aleatoric) uncertainty.

Autonomous Vehicles Binary Classification +2

Perturbation Analysis of Neural Collapse

no code implementations • 29 Oct 2022 • Tom Tirer, Haoxiang Huang, Jonathan Niles-Weed

In this paper, we propose a richer model that can capture this phenomenon by forcing the features to stay in the vicinity of a predefined features matrix (e. g., intermediate features).

Neural Network with Local Converging Input (NNLCI) for Supersonic Flow Problems with Unstructured Grids

no code implementations • 23 Oct 2023 • Weiming Ding, Haoxiang Huang, Tzu Jung Lee, Yingjie Liu, Vigor Yang

In the present study, we develop a neural network with local converging input (NNLCI) for high-fidelity prediction using unstructured data.