Jovana Mitrovi'c

Artificial Intelligence · 2018–2025

A researcher in the Science corpus: 7 papers; trusts 324 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 147 citations into it; #27,753 of 35,345 by trust here, #14,181 by citations
• Computer Vision and Pattern Recognition — 103 citations into it; #17,117 of 21,575 by trust here, #14,151 by citations
• Reinforcement Learning — 55 citations into it
• Representation & Self-Supervised Learning — 47 citations into it
• Generative Models — 29 citations into it
• Causal Inference & Discovery — 24 citations into it
• Optimization & Training — 23 citations into it
• Meta & Continual Learning — 20 citations into it

Whom Jovana Mitrovi'c trusts overall

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

1. Dominik Janzing
2. Bernhard Schölkopf
3. Jan Peters
4. Geoffrey E. Hinton
5. Diederik P. Kingma
6. Alex Krizhevsky
7. Kaiming He
8. Yoshua Bengio
9. Tom L. Burr
10. Yann LeCun

Who trusts Jovana Mitrovi'c overall

1. Xiao Wang
2. Nan Rosemary Ke
3. Murray Shanahan
4. Jindong Wang
5. Lin Guan
6. Gerald Woo
7. Guo-Jun Qi
8. Olexa Bilaniuk
9. Christos Kaplanis
10. Bernhard Schölkopf

Papers from Jovana Mitrovi'c's perspective

Ordered by how strongly the researchers Jovana Mitrovi'c trusts endorse each paper. Same corpus, a different order for every researcher.

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

Their papers

• Causal Reasoning from Meta-reinforcement Learning (2019) — 138 citations
• Causally Correct Partial Models for Reinforcement Learning (2020) — 36 citations
• Representation Learning via Invariant Causal Mechanisms (2020) — 290 citations
• Encoders and Ensembles for Task-Free Continual Learning (2021) — 26 citations
• Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities (2025) — 3,609 citations
• Causal Inference via Kernel Deviance Measures (2018) — 68 citations
• Hierarchical Adversarially Learned Inference (2018) — 29 citations