Harishchandra Dubey
Signal Processing · 2020–2023
A researcher in the Science corpus: 7 papers; trusts 13 researchers and is trusted by 7 researchers here, as inferred from the citation graph.
Subfields
- Signal Processing — 112 citations into it; #3,448 of 7,572 by trust here, #1,504 by citations
- Artificial Intelligence — 54 citations into it; #23,115 of 35,345 by trust here, #14,438 by citations
- Speech & Audio — 38 citations into it; #1,026 of 1,076 by trust here, #980 by citations
- Computational Mechanics — 34 citations into it
- Cognitive Neuroscience — 33 citations into it
- Biomedical Engineering — 13 citations into it; #7,869 of 10,734 by trust here, #5,112 by citations
Whom Harishchandra Dubey trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Chandan K. A. Reddy
- Ross Cutler
- Jean-Marc Valin
- Babak Naderi
- Jort Florent Gemmeke
- Sebastian Braun
- Vishak Gopal
- Tom Ko
- Hyeong-Seok Choi
- Joon Son Chung
Who trusts Harishchandra Dubey overall
- Ross Cutler
- Chandan K. A. Reddy
- Babak Naderi
- Hubert Siuzdak
- Vishak Gopal
- Xue Jiang
- Xiaofei Wang
- Tianrui Wang
Papers from Harishchandra Dubey's perspective
Ordered by how strongly the researchers Harishchandra Dubey trusts endorse each paper. Same corpus, a different order for every researcher.
- Long Short-Term Memory
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Attention is All you Need (Neural Information Processing Systems)
- Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation
- ImageNet: A large-scale hierarchical image database
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Going deeper with convolutions
Their papers
- The INTERSPEECH 2020 Deep Noise Suppression Challenge: Datasets, Subjective Testing Framework, and Challenge Results (2020) — 460 citations
- Interspeech 2021 Deep Noise Suppression Challenge (2021) — 206 citations
- Icassp 2022 Deep Noise Suppression Challenge (2022) — 237 citations
- ICASSP 2023 Deep Noise Suppression Challenge (2023) — 193 citations
- Weighted Speech Distortion Losses for Neural-Network-Based Real-Time Speech Enhancement (2020) — 137 citations
- ICASSP 2021 Deep Noise Suppression Challenge (2020) — 161 citations
- The INTERSPEECH 2020 Deep Noise Suppression Challenge: Datasets, Subjective Speech Quality and Testing Framework (2020) — 91 citations