Yashas Annadani

Artificial Intelligence · 2020–2021

A researcher in the Science corpus: 2 papers; trusts 25 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 37 citations into it
• Computer Vision and Pattern Recognition — 18 citations into it
• Representation & Self-Supervised Learning — 16 citations into it
• Causal Inference & Discovery — 15 citations into it
• Probabilistic & Bayesian Methods — 14 citations into it
• Generative Models — 9 citations into it

Whom Yashas Annadani trusts overall

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

1. Ronald J. Williams
2. Diederik P. Kingma
3. Bernhard Schölkopf
4. Tom L. Burr
5. Jack Kuipers
6. Yoshua Bengio
7. Sepp Hochreiter
8. David Maxwell Chickering
9. Geoffrey E. Hinton
10. J. Urgen Schmidhuber

Who trusts Yashas Annadani overall

1. Tristan Deleu

Papers from Yashas Annadani's perspective

Ordered by how strongly the researchers Yashas Annadani 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. Attention is All you Need (Neural Information Processing Systems)
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. Auto-Encoding Variational Bayes (International Conference on Learning Representations)
10. GENERATIVE ADVERSARIAL NETS

Their papers

• Variational Causal Networks: Approximate Bayesian Inference over Causal Structures (2021) — 61 citations
• Structural Autoencoders Improve Representations for Generation and Transfer (2020) — 13 citations