Maneesh Sahani
Cognitive Neuroscience · 2000–2022
A researcher in the Science corpus: 15 papers; trusts 72 researchers and is trusted by 56 researchers here, as inferred from the citation graph.
Subfields
- Cognitive Neuroscience — 69 citations into it; #2,080 of 10,852 by trust here, #1,210 by citations
- Artificial Intelligence — 59 citations into it; #5,175 of 35,345 by trust here, #8,999 by citations
- Cellular and Molecular Neuroscience — 24 citations into it; #538 of 2,998 by trust here, #381 by citations
- Computer Vision and Pattern Recognition — 24 citations into it
- Probabilistic & Bayesian Methods — 24 citations into it; #662 of 1,525 by trust here, #688 by citations
- Representation & Self-Supervised Learning — 18 citations into it
- Signal Processing — 16 citations into it; #5,105 of 7,572 by trust here, #5,340 by citations
- Electrical and Electronic Engineering — 14 citations into it; #4,593 of 16,539 by trust here, #5,046 by citations
Whom Maneesh Sahani trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- David John Cameron MacKay
- Radford M. Neal
- Ilya Sutskever
- Michael I. Jordan
- Andriy Mnih
- Yoshua Bengio
- Matthew J. Beal
- Tommi S. Jaakkola
- Alex Krizhevsky
Who trusts Maneesh Sahani overall
- Yarin Gal
- Thang D. Bui
- Richard E. Turner
- Andrew Gordon Wilson
- Yingzhen Li
- Zoubin Ghahramani
- Rohollah Soltani
- Meire Fortunato
- Behnam Neyshabur
- Noel Loo
Papers from Maneesh Sahani's perspective
Ordered by how strongly the researchers Maneesh Sahani trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Learning Multiple Layers of Features from Tiny Images
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- Two problems with variational expectation maximisation for time-series models (2011) — 222 citations
- Regularization and nonlinearities for neural language models: when are they needed? (2013) — 47 citations
- Fast Gaussian process methods for point process intensity estimation (2008) — 126 citations
- Deep learning, reinforcement learning, and world models (2022) — 503 citations
- Temporal structure in neuronal activity during working memory in macaque parietal cortex (2000) — 1,103 citations
- Organizing recurrent network dynamics by task-computation to enable continual learning (2020) — 98 citations
- A Universal Marginalizer for Amortized Inference in Generative Models (2017) — 31 citations
- Cortical control of arm movements: a dynamical systems perspective. (2013) — 810 citations
- Stimulus onset quenches neural variability: a widespread cortical phenomenon (2010) — 1,116 citations
- A Structured Model of Video Reproduces Primary Visual Cortical Organisation (2009) — 44 citations
- Nonlinearities and Contextual Influences in Auditory Cortical Responses Modeled with Multilinear Spectrotemporal Methods (2008) — 148 citations
- Expectation Propagation for Inference in Non-Linear Dynamical Models with Poisson Observations (2006) — 16 citations
- Algorithmic Self-Assembly of DNA (2006) — 410 citations
- Localization bias and spatial resolution of adaptive and non-adaptive spatial filters for MEG source reconstruction (2005) — 480 citations
- Functional, but Not Anatomical, Separation of "what" and "when" in Prefrontal Cortex Gaussian-process Factor Analysis for Low-dimensional Single-trial Analysis of Neural Population Activity