(ICLR 2022 Spotlight) Official PyTorch implementation of "How Do Vision Transformers Work?"
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Jul 14, 2022 - Python
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loss-landscape
Here are 15 public repositories matching this topic...
Create animations for the optimization trajectory of neural nets
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Jan 30, 2024 - Python
Explores the ideas presented in Deep Ensembles: A Loss Landscape Perspective (https://arxiv.org/abs/1912.02757) by Stanislav Fort, Huiyi Hu, and Balaji Lakshminarayanan.
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Jul 29, 2020 - Jupyter Notebook
Implements sharpness-aware minimization (https://arxiv.org/abs/2010.01412) in TensorFlow 2.
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Nov 11, 2021 - Jupyter Notebook
This repository contains the code and models for our paper "Investigating and Mitigating Failure Modes in Physics-informed Neural Networks(PINNs)"
constrained-optimization neural-networks differential-equations lagrange-multipliers unconstrained-optimization adaptive-optimizer loss-landscape
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Dec 8, 2023 - Jupyter Notebook
[TMLR] "Can You Win Everything with Lottery Ticket?" by Tianlong Chen, Zhenyu Zhang, Jun Wu, Randy Huang, Sijia Liu, Shiyu Chang, Zhangyang Wang
uncertainty interpretability robustness generalization out-of-distribution-detection pac-bayes lottery-ticket-hypothesis explanability flatness adversarial-robustness winning-tickets loss-landscape
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Sep 8, 2022 - Python
analytic solution to the git-merge algorithm, derived from "Git Re-Basin: Merging Models modulo Permutation Symmetries"
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Jul 13, 2023 - Jupyter Notebook
[NeurIPS 2021] Towards Better Understanding of Training Certifiably Robust Models against Adversarial Examples | ⛰️
robustness smoothness adversarial-machine-learning adversarial-examples adversarial-attacks robustness-verification loss-landscape certified-defense certified-training
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Jul 11, 2022 - Python
Source code for NeurIPS-2024 paper "Where Do Large Learning Rates Lead Us"
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Dec 14, 2024 - Jupyter Notebook
[Int. J. Comput. Vis. 2024] Revisiting Deep Ensemble for Out-of-Distribution Detection: A Loss Landscape Perspective
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Jul 18, 2024 - Python
Worth-reading papers and related awesome resources on deep learning optimization algorithms. 值得一读的深度学习优化器论文与相关资源。
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Mar 24, 2023 - Python
Surrogate Gap Guided Sharpness-Aware Minimization (GSAM) implementation for keras/tensorflow 2
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Jul 13, 2023 - Python
Visualize loss landscape
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Jun 19, 2020 - Julia
This project builds on recent research that explores the phenomenon of Grokking. The goal is to investigate when, why, and how grokking occurs, focusing on transformers under various batch sizes.
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Oct 18, 2024 - Python
Code for NeurIPS 2024 paper "Only Strict Saddles in the Energy Landscape of Predictive Coding Networks?"
deep-neural-networks deep-learning gradient-descent backpropagation predictive-coding local-learning saddle-point loss-landscape vanishing-gradient inference-learning
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Dec 13, 2024 - Jupyter Notebook
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