Arun Ahuja
Artificial Intelligence · 2018–2023
A researcher in the Science corpus: 12 papers; trusts 103 researchers and is trusted by 34 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 234 citations into it; #6,689 of 35,345 by trust here, #2,646 by citations
- Reinforcement Learning — 206 citations into it; #698 of 2,242 by trust here, #288 by citations
- Computer Vision and Pattern Recognition — 103 citations into it
- Control and Systems Engineering — 64 citations into it
- Management Science and Operations Research — 34 citations into it; #1,916 of 11,946 by trust here, #301 by citations
- Optimization & Training — 33 citations into it
- Computational Theory and Mathematics — 31 citations into it
- Biomedical Engineering — 29 citations into it
Whom Arun Ahuja trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Diederik P. Kingma
- Geoffrey E. Hinton
- Kaiming He
- Richard S. Sutton
- Yoshua Bengio
- Alex Krizhevsky
- Yann LeCun
- Karen Simonyan
- Ilya Sutskever
- Ross B. Girshick
Who trusts Arun Ahuja overall
- Xisen Jin
- Rahaf Aljundi
- Lucas Caccia
- Arslan Chaudhry
- Josh Merel
- B. Ermiş
- Massimo Caccia
- Caglar Gulcehre
- Oleksiy Ostapenko
- Gyuhak Kim
Papers from Arun Ahuja's perspective
Ordered by how strongly the researchers Arun Ahuja 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)
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- GENERATIVE ADVERSARIAL NETS
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- Learning Multiple Layers of Features from Tiny Images
Their papers
- Experience Replay for Continual Learning (2018) — 1,717 citations
- Unsupervised Predictive Memory in a Goal-Directed Agent (2018) — 206 citations
- V-MPO: On-Policy Maximum a Posteriori Policy Optimization for Discrete and Continuous Control (2019) — 141 citations
- Hierarchical visuomotor control of humanoids (2018) — 102 citations
- Imitating Interactive Intelligence (2020) — 74 citations
- Optimizing agent behavior over long time scales by transporting value (2018) — 139 citations
- Exploiting Hierarchy for Learning and Transfer in KL-regularized RL (2019) — 45 citations
- Catch & Carry (2019) — 103 citations
- Collaborating with language models for embodied reasoning (2023) — 91 citations
- Neural probabilistic motor primitives for humanoid control (2018) — 187 citations
- Genomic features of response to combination immunotherapy in patients with advanced non-small cell lung cancer (2018) — 921 citations
- Probing Physics Knowledge Using Tools from Developmental Psychology (2018) — 38 citations