Companion code for the research paper "CoAug: Combining Augmentation of Labels and Labeling Rules"

Integration of selected post-quantum schemes into the embedded TLS library wolfSSL as part of our paper "Mixed Certificate Chains for the Transition to Post-Quantum Authentication in TLS 1.3"

This is the code accompanying the AAAI 2022 paper "Ranking Info Noise Contrastive Estimation: Boosting Contrastive Learning via Ranked Positives" https://arxiv.org/abs/2201.11736 . The method allows you to use additional ranking information for representation learning.

Official Implementation of the paper "Multi-Attribute Open Set Recognition" (GCPR 2022)

Official Implementation of the paper "Overcoming Shortcut Learning in a Target Domain by Generalizing Basic Visual Factors from a Source Domain" (ECCV 2022)

Code accompanying the ICLR 2021 paper "ResNet After All? Neural ODEs and Their Numerical Solution"

Coder of the paper 'Latent Outlier Exposure for Anomaly Detectin with Contaminated Data' published in ICML 2022

BCAI ART : Bosch Center for AI Adversarial Robustness Toolkit

[CVPR 2022] What Matters For Meta-Learning Vision Regression Tasks?

Code of the paper 'Raising the Bar in Graph-level Anomaly Detection' published in IJCAI-2022

Code of the paper 'Neural Transformation Learning for Anomaly Detection' published in ICML 2021

Official Implementation of the paper "A U-Net Based Discriminator for Generative Adversarial Networks" (CVPR 2020)

This is the HEE (Highway Eagle Eye) data set. It consists of ~12000 individual vehicle trajectories (~4h), recorded by drones over a highway section (length ~600m) with an entry lane.

Dataset of a collection of commonsense knowledge assertions relevant for the autonomous driving (AD) domain.

Material for the paper "Micromechanical fatigue experiments for validation of microstructure-sensitive fatigue simulation models".

Official PyTorch implementation of the paper "SOSP: Efficiently Capturing Global Correlations by Second-Order Structured Pruning"

Source code for Bechtold et al., "Fostering Generalization in Single-view 3D Reconstruction by Learning a Hierarchy of Local and Global Shape Priors", CVPR 2021.

This will be the companion code for the benchmarking study reported in the paper Transfer Learning with Gaussian Processes for Bayesian Optimization accepted for publication at AISTATS 2022

The Hybrid Modeling Notebook