Vinay Venkatesh Ramasesh
Artificial Intelligence · 2016–2025
A researcher in the Science corpus: 10 papers; trusts 109 researchers and is trusted by 9 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 99 citations into it; #17,527 of 35,345 by trust here, #3,907 by citations
- Computer Vision and Pattern Recognition — 25 citations into it; #11,110 of 21,575 by trust here, #13,542 by citations
- Representation & Self-Supervised Learning — 10 citations into it; #1,851 of 3,145 by trust here, #2,330 by citations
- Model Architectures — 8 citations into it
- Optimization & Training — 8 citations into it
- Reinforcement Learning — 6 citations into it
Whom Vinay Venkatesh Ramasesh trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Kaiming He
- Geoffrey E. Hinton
- Karen Simonyan
- Yoshua Bengio
- Alex Krizhevsky
- Diederik P. Kingma
- Yann LeCun
- Andrew Zisserman
- Ilya Sutskever
- Ian J. Goodfellow
Who trusts Vinay Venkatesh Ramasesh overall
- Timothée Lesort
- Quang Pham
- James Smith
- Sebastian Lee
- Minh-Hieu Phan
- Liyuan Wang
- Seyed Iman Mirzadeh
- Oleksiy Ostapenko
- Andrei Stoian
- Chenghao Liu
Papers from Vinay Venkatesh Ramasesh's perspective
Ordered by how strongly the researchers Vinay Venkatesh Ramasesh trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
- Learning Multiple Layers of Features from Tiny Images
Their papers
- Solving Quantitative Reasoning Problems with Language Models (2022) — 1,845 citations
- Anatomy of Catastrophic Forgetting: Hidden Representations and Task Semantics (2020) — 216 citations
- Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context (2024) — 3,818 citations
- Computation of Molecular Spectra on a Quantum Processor with an Error-Resilient Algorithm (2017) — 449 citations
- Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities (2025) — 3,609 citations
- Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models (2023) — 266 citations
- Effect of scale on catastrophic forgetting in neural networks (2022) — 226 citations
- Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models (2022) — 2,561 citations
- Caliban: Docker-based job manager for reproducible workflows (2020) — 7 citations
- Observing Topological Invariants Using Quantum Walks in Superconducting Circuits (2016) — 146 citations