Neural Additive Models - Visualization Tool in PyTorch/Plotly-Dash
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Updated
Mar 3, 2023 - Python
Neural Additive Models - Visualization Tool in PyTorch/Plotly-Dash
[AAAI 2023] An official PyTorch implementation of paper 'READ: Aggregating Reconstruction Error into Out-of-distribution Detection'
Unofficial implementation of paper "Flexibly Fair Representation Learning by Disentanglement"
Package to accelerate research on generalized out-of-distribution (OOD) detection.
[AAAI'23 Paper] A machine learning defense for auditors of black box automated decision-making systems.
Scripts to process the reference framework into an object
Code for paper "FreezeAsGuard: Mitigating Illegal Adaptation of Diffusion Models via Selective Tensor Freezing"
An open source web platform for assessing Responsible and Trustworthy AI maturity level
Optimization-based deep learning models can give explainability with output guarantees and certificates of trustworthiness.
Breaking the Trilemma of Privacy, Utility, Efficiency via Controllable Machine Unlearning
Multi-omics Trustworthy Integration Framework (MoTIF)
Evaluation & testing framework for computer vision models
AutoML system for building trustworthy peptide bioactivity predictors
Code for Highly Trustworthy Multimodal Learning (HTML) Method on Omics
Code of the paper: Finetuning Text-to-Image Diffusion Models for Fairness
EditBias: Debiasing Stereotyped Language Models via Model Editing
[ICML 2024] Prompting4Debugging: Red-Teaming Text-to-Image Diffusion Models by Finding Problematic Prompts (Official Pytorch Implementation)
Code for the Paper "A Functional Data Perspective and Baseline on Multi-Layer Out-of-Distribution Detection"
Code for the paper "Coherent Concept-based Explanations in Medical Image and Its Application to Skin Lesion Diagnosis", CVPRW 2023.
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