Predict dense depth maps from sparse and noisy LiDAR frames guided by RGB images. (Ranked 1st place on KITTI) [MVA 2019]

Code for MentorNet: Learning Data-Driven Curriculum for Very Deep Neural Networks

[ICML2020] Normalized Loss Functions for Deep Learning with Noisy Labels

AAAI 2021: Beyond Class-Conditional Assumption: A Primary Attempt to Combat Instance-Dependent Label Noise

AAAI 2021: Robustness of Accuracy Metric and its Inspirations in Learning with Noisy Labels

MIL-RBERT: A Data-driven Approach for Noise Reduction in Distantly Supervised Biomedical Relation Extraction (BioNLP @ ACL 2020)

Dynamic Mixing For Speech Processing (mix-on-the-fly)

Code from paper High-throughput Onboard Hyperspectral Image Compression with Ground-based CNN Reconstruction

A collection of algorithms for detecting and handling label noise

Official implementation of our paper: "COLA: Leveraging Local and Global Relationships for Corrupted Label Detection"

Enhanced awesome-align for low-resource languages and noise simulation: https://arxiv.org/abs/2301.09685

Self-Supervised Learning for Outlier Detection.

🍷 Code for Noisy Pairing and Partial Supervision for Stylized Opinion Summarization (Iso et al; INLG 2024)

Implementations of various NMF algorithms on the ORL and cropped YaleB datasets.

Official code for "NoRD: A Framework for Noise-Resilient Self-Distillation through Relative Supervision" Published at Applied Intelligence Journal

Estimate Trend at a Point in a Noisy Time Series

Least squares and recursive least squares implementation. 2D line fit to noisy data.

Methods for numerical differentiation of noisy data in python

Robust Multi-Task Gradient Boosting