Giri Panamoottil Krishnan

Cognitive Neuroscience · 2016–2021

A researcher in the Science corpus: 9 papers; trusts 143 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

• Cognitive Neuroscience — 236 citations into it; #4,225 of 10,852 by trust here, #3,648 by citations
• Cellular and Molecular Neuroscience — 136 citations into it
• Artificial Intelligence — 129 citations into it
• Computer Vision and Pattern Recognition — 81 citations into it
• Neuroscience — 61 citations into it
• Meta & Continual Learning — 55 citations into it
• Experimental and Cognitive Psychology — 39 citations into it
• Representation & Self-Supervised Learning — 22 citations into it

Whom Giri Panamoottil Krishnan trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Geoffrey E. Hinton
2. Kaiming He
3. Yann LeCun
4. Yoshua Bengio
5. Alex Krizhevsky
6. Ronald Kemker
7. David A. McCormick
8. Anthony V. Robins
9. Yina Wei
10. J. Urgen Schmidhuber

Who trusts Giri Panamoottil Krishnan overall

1. Maxim Bazhenov
2. Timothy Tadros
3. Pavel Sanda
4. Ryan Golden
5. Tyler L. Hayes
6. Rui Gao
7. Ramyaa Ramyaa
8. Jean Erik Delanois

Papers from Giri Panamoottil Krishnan's perspective

Ordered by how strongly the researchers Giri Panamoottil Krishnan trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Gradient-based learning applied to document recognition
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. ImageNet Large Scale Visual Recognition Challenge
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Can sleep protect memories from catastrophic forgetting? (2019) — 64 citations
• Replay in Deep Learning: Current Approaches and Missing Biological Elements (2021) — 152 citations
• Biologically inspired sleep algorithm for increased generalization and adversarial robustness in deep neural networks (2020) — 28 citations
• Bidirectional Interaction of Hippocampal Ripples and Cortical Slow Waves Leads to Coordinated Spiking Activity During NREM Sleep. (2020) — 31 citations
• Biologically Inspired Sleep Algorithm for Reducing Catastrophic Forgetting in Neural Networks (2020) — 7 citations
• Biologically inspired sleep algorithm for artificial neural networks (2019) — 21 citations
• Differential roles of sleep spindles and sleep slow oscillations in memory consolidation (2017) — 84 citations
• Cellular and neurochemical basis of sleep stages in the thalamocortical network (2016) — 89 citations
• Synaptic Mechanisms of Memory Consolidation during Sleep Slow Oscillations (2016) — 92 citations