Object detection on multiple datasets with an automatically learned unified label space.
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Updated
Mar 8, 2024 - Python
Object detection on multiple datasets with an automatically learned unified label space.
A certifiable defense against adversarial examples by training neural networks to be provably robust
Official TensorFlow Implementation of Adversarial Training for Free! which trains robust models at no extra cost compared to natural training.
Official repository of STYLER: Style Factor Modeling with Rapidity and Robustness via Speech Decomposition for Expressive and Controllable Neural Text to Speech, INTERSPEECH 2021
Python package to transfer data in a fast, reliable, and packetized form
Robust Kalman filter with adaptive noise statistics estimation.
[ICRA2023] CoAlign: Robust Collaborative 3D Object Detection in Presence of Pose Errors
ICML 2019: Understanding and Utilizing Deep Neural Networks Trained with Noisy Labels
PyVESC is an easy to use and robust Python implementation of the VESC - Open Source ESC communication protocol
PyTorch Implementation of Google Brain's WaveGrad 2: Iterative Refinement for Text-to-Speech Synthesis
[Nature Machine Intelligence Journal] Official pytorch implementation for Uncertainty-Guided Dual-Views for Semi-Supervised Volumetric Medical Image Segmentation
IPCCC 2018: Robust and Unsupervised KPI Anomaly Detection Based on Conditional Variational Autoencoder
[ACM MM22] Towards Robust Video Object Segmentation with Adaptive Object Calibration, ACM Multimedia 2022
CFEA: Collaborative Feature Ensembling Adaptation for Domain Adaptation in Unsupervised Optic Disc and Cup Segmentation
PyTorch Implementation of Robust and fine-grained prosody control of end-to-end speech synthesis
An open source python library for magnetotelluric robust processing.
FAVITES (FrAmework for VIral Transmission and Evolution Simulation)
Fast and differentiable geometric median, a multivariate median analogue. Install with `pip install geom-median`
Implementation of "Bayesian Robust Attributed Graph Clustering: Joint Learning of Partial Anomalies and Group Structure".
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