Noisy Input

Noisy input, a pervasive challenge across diverse scientific domains, focuses on developing robust methods for processing and analyzing data contaminated with errors or uncertainties. Current research emphasizes improving model resilience to noise through techniques like data augmentation, noise filtering (e.g., input denoising), and the development of inherently robust algorithms (e.g., Bayesian approaches, M-estimators), often within specific model architectures such as neural networks, memristor-based systems, and diffusion models. Addressing noisy input is crucial for enhancing the reliability and accuracy of machine learning models and other data-driven methods across applications ranging from quantum computing and human pose estimation to speech processing and scientific simulations.

Papers

September 11, 2024

Learning Robust Observable to Address Noise in Quantum Machine Learning
Bikram Khanal, Pablo Rivas
Quantum Machine Learning Robust Learning Intermediate Scale Quantum Quantum Machine Learning Model Quantum System Quantum Computation Noisy Input

August 26, 2024

On-Chip Learning with Memristor-Based Neural Networks: Assessing Accuracy and Efficiency Under Device Variations, Conductance Errors, and Input Noise
M. Reza Eslami, Dhiman Biswas, Soheib Takhtardeshir, Sarah S. Sharif, Yaser M. Banad
Neural Network Memristive Device Computing in Memory Noisy Input Device Variation Better on Chip Data Circuit Fidelity

February 4, 2024

Controller Synthesis from Noisy-Input Noisy-Output Data
Lidong Li, Andrea Bisoffi, Claudio De Persis, Nima Monshizadeh
Linear System M$ Base Controller Controller Synthesis Noisy Input Input Output Multi Input Multi Output Output Feedback

December 11, 2023

Improving the Robustness of 3D Human Pose Estimation: A Benchmark and Learning from Noisy Input
Trung-Hieu Hoang, Mona Zehni, Huy Phan, Duc Minh Vo, Minh N. Do
LeArning Abstract Native Robustness New Benchmark 3D Human Pose Estimation Gaussian Noise Noisy Input Confidence Map 3D Camera Pose Lifting

November 19, 2023

Uncertainty quantification for noisy inputs-outputs in physics-informed neural networks and neural operators
Zongren Zou, Xuhui Meng, George Em Karniadakis
Physic Informed Neural Network Uncertainty Quantification Neural Operator Scientific Machine Learning Bayesian Inverse Problem Noisy Input Linear Surrogate

November 6, 2023

Safe Collective Control under Noisy Inputs and Competing Constraints via Non-Smooth Barrier Functions
Clinton Enwerem, John S. Baras
Control Barrier Function Noisy Input CBF Based Collective Control Stochastic Model Predictive

October 21, 2023

Finite-context Indexing of Restricted Output Space for NLP Models Facing Noisy Input
Minh Nguyen, Nancy F. Chen
Natural Language Processing NLP Model Structured Output Noisy Input

June 5, 2023

A Deep Learning Approach Utilizing Covariance Matrix Analysis for the ISBI Edited MRS Reconstruction Challenge
Julian P. Merkofer, Dennis M. J. van de Sande, Sina Amirrajab, Gerhard S. Drenthen, Mitko Veta, Jacobus F. A. Jansen, Marcel Breeuwer, Ruud J. G. van Sloun
Machine Learning Model Magnetic Resonance Noisy Input Covariance Neural Network Ex Vivo Magnetic Resonance Spectroscopic Imaging Sample Covariance Matrix

May 26, 2023

Double Descent and Overfitting under Noisy Inputs and Distribution Shift for Linear Denoisers
Chinmaya Kausik, Kashvi Srivastava, Rishi Sonthalia
Training Data Distribution Shift Denoising Process Model Overfitting Double Descent Noisy Input Supervised Denoising

March 13, 2023

A two-stage speaker extraction algorithm under adverse acoustic conditions using a single-microphone
Aviad Eisenberg, Sharon Gannot, Shlomo E. Chazan
Speech Dereverberation Acoustic Environment Speaker Extraction Noisy Input

February 20, 2023

Improving User Controlled Table-To-Text Generation Robustness
Hanxu Hu, Yunqing Liu, Zhongyi Yu, Laura Perez-Beltrachini
Natural Language Description Noisy Input Natural Language Generator

February 7, 2023

High-Resolution GAN Inversion for Degraded Images in Large Diverse Datasets
Yanbo Wang, Chuming Lin, Donghao Luo, Ying Tai, Zhizhong Zhang, Yuan Xie
GAN Inversion Degraded Image Image Collection State of the Art Datasets Noisy Input GAN Algorithm Regularized Newton Raphson Inversion

December 20, 2022

Improving the Robustness of Summarization Models by Detecting and Removing Input Noise
Kundan Krishna, Yao Zhao, Jie Ren, Balaji Lakshminarayanan, Jiaming Luo, Mohammad Saleh, Peter J. Liu
Native Robustness Summarization Model Model Inference Abstractive Summarization Model Noisy Input

November 7, 2022

Robust Total Least Mean M-Estimate normalized subband filter Adaptive Algorithm for impulse noises and noisy inputs
Haiquan Zhao, Zian Cao, Yida Chen
Adaptive Filter Noisy Input Impulsive Noise Robust Mean Estimation Deep Subband

October 31, 2022

Magnitude or Phase? A Two Stage Algorithm for Dereverberation
Ayal Schwartz, Sharon Gannot, Shlomo E. Chazan
Two Stage Speech Dereverberation Civil Engineering Phase Earthquake Magnitude Noisy Input

May 8, 2022

On Conditioning the Input Noise for Controlled Image Generation with Diffusion Models
Vedant Singh, Surgan Jandial, Ayush Chopra, Siddharth Ramesh, Balaji Krishnamurthy, Vineeth N. Balasubramanian
Diffusion Model Consistent Conditioning Object Generation Noisy Input

March 6, 2022

CNN self-attention voice activity detector
Amit Sofer, Shlomo E. Chazan
Convolutional Neural Network Receptive Field Voice Activity Detection Noisy Input

February 15, 2022

Robust Multi-Objective Bayesian Optimization Under Input Noise
Samuel Daulton, Sait Cakmak, Maximilian Balandat, Michael A. Osborne, Enlu Zhou, Eytan Bakshy
Bayesian Optimization Multiple Objective Optimal Design Multi Objective Bayesian Optimization Noisy Input

November 19, 2021

Enhanced countering adversarial attacks via input denoising and feature restoring
Yanni Li, Wenhui Zhang, Jiawei Liu, Xiaoli Kou, Hui Li, Jiangtao Cui
Adversarial Attack Adversarial Example Black Box Adversarial Attack Noisy Input

November 9, 2021

Learning Numerical Action Models from Noisy Input Data
José Á. Segura-Muros, Juan Fernández-Olivares, Raúl Pérez
Action Model Noisy Input

Noisy Input

Papers

Learning Robust Observable to Address Noise in Quantum Machine Learning

On-Chip Learning with Memristor-Based Neural Networks: Assessing Accuracy and Efficiency Under Device Variations, Conductance Errors, and Input Noise

Controller Synthesis from Noisy-Input Noisy-Output Data

Improving the Robustness of 3D Human Pose Estimation: A Benchmark and Learning from Noisy Input

Uncertainty quantification for noisy inputs-outputs in physics-informed neural networks and neural operators

Safe Collective Control under Noisy Inputs and Competing Constraints via Non-Smooth Barrier Functions

Finite-context Indexing of Restricted Output Space for NLP Models Facing Noisy Input

A Deep Learning Approach Utilizing Covariance Matrix Analysis for the ISBI Edited MRS Reconstruction Challenge

Double Descent and Overfitting under Noisy Inputs and Distribution Shift for Linear Denoisers

A two-stage speaker extraction algorithm under adverse acoustic conditions using a single-microphone

Improving User Controlled Table-To-Text Generation Robustness

High-Resolution GAN Inversion for Degraded Images in Large Diverse Datasets

Improving the Robustness of Summarization Models by Detecting and Removing Input Noise

Robust Total Least Mean M-Estimate normalized subband filter Adaptive Algorithm for impulse noises and noisy inputs

Magnitude or Phase? A Two Stage Algorithm for Dereverberation

On Conditioning the Input Noise for Controlled Image Generation with Diffusion Models

CNN self-attention voice activity detector

Robust Multi-Objective Bayesian Optimization Under Input Noise

Enhanced countering adversarial attacks via input denoising and feature restoring

Learning Numerical Action Models from Noisy Input Data