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Compressed Sensing

72 directly classified papers

Papers per year

Papers

Non-Convex Tensor Recovery from Local Measurements AAAI 2025
CPP-Net: Embracing Multi-Scale Feature Fusion into Deep Unfolding CP-PPA Network for Compressive Sensing CVPR 2024
Tensor Compressive Sensing Fused Low-Rankness and Local-Smoothness AAAI 2023
Neural Circuits for Fast Poisson Compressed Sensing in the Olfactory Bulb NIPS 2023
Cost-efficient Gaussian tensor network embeddings for tensor-structured inputs NIPS 2022
Signal Recovery with Non-Expansive Generative Network Priors NIPS 2022
Multi-layer State Evolution Under Random Convolutional Design NIPS 2022
Non-Iterative Recovery From Nonlinear Observations Using Generative Models CVPR 2022
Sharp Restricted Isometry Property Bounds for Low-Rank Matrix Recovery Problems with Corrupted Measurements AAAI 2022
Equivariant Priors for compressed sensing with unknown orientation ICML 2022
Dynamic Sasvi: Strong Safe Screening for Norm-Regularized Least Squares NIPS 2021
On learning sparse vectors from mixture of responses NIPS 2021
Towards Sample-Optimal Compressive Phase Retrieval with Sparse and Generative Priors NIPS 2021
Learning sparse codes from compressed representations with biologically plausible local wiring constraints NIPS 2020
Sample Complexity Bounds for 1-bit Compressive Sensing and Binary Stable Embeddings with Generative Priors ICML 2020
Phase retrieval in high dimensions: Statistical and computational phase transitions NIPS 2020
Robust Low-Rank Discovery of Data-Driven Partial Differential Equations AAAI 2020
Deep Compressed Sensing ICML 2019
Generalization Error Analysis of Quantized Compressive Learning NIPS 2019
Random Projections with Asymmetric Quantization NIPS 2019
Superset Technique for Approximate Recovery in One-Bit Compressed Sensing NIPS 2019
Decentralized sketching of low rank matrices NIPS 2019
Universality in Learning from Linear Measurements NIPS 2019
Learning a Compressed Sensing Measurement Matrix via Gradient Unrolling ICML 2019
Plug-in Estimation in High-Dimensional Linear Inverse Problems: A Rigorous Analysis NIPS 2018