Julian Togelius
Artificial Intelligence · 2007–2023
A researcher in the Science corpus: 21 papers; trusts 233 researchers and is trusted by 39 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 206 citations into it; #4,749 of 35,345 by trust here, #4,512 by citations
- Reinforcement Learning — 104 citations into it
- Computer Vision and Pattern Recognition — 71 citations into it; #10,382 of 21,575 by trust here, #7,852 by citations
- Evaluation & Benchmarks — 27 citations into it; #2,230 of 3,147 by trust here, #2,482 by citations
- Model Architectures — 27 citations into it; #1,599 of 2,278 by trust here, #1,421 by citations
- Natural Language Processing — 24 citations into it
- Management Science and Operations Research — 23 citations into it
- Representation & Self-Supervised Learning — 21 citations into it
Whom Julian Togelius trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Kenneth O. Stanley
- J. Urgen Schmidhuber
- Geoffrey E. Hinton
- Yoshua Bengio
- Ilya Sutskever
- Alex Graves
- Diederik P. Kingma
- Alex Krizhevsky
- Sepp Hochreiter
- Yann LeCun
Who trusts Julian Togelius overall
- Sebastian Risi
- Georgios N. Yannakakis
- J. Urgen Schmidhuber
- Matthew J. Guzdial
- Rui Wang
- Ahmed Hussein
- David R Ha
- Joel Lehman
- Gabriel Synnaeve
- Nadav Bhonker
Papers from Julian Togelius's perspective
Ordered by how strongly the researchers Julian Togelius 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
- Attention is All you Need (Neural Information Processing Systems)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Learning Multiple Layers of Features from Tiny Images
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- Evolving Memory Cell Structures for Sequence Learning (2009) — 106 citations
- Illuminating Generalization in Deep Reinforcement Learning through Procedural Level Generation (2018) — 205 citations
- Obstacle Tower: A Generalization Challenge in Vision, Control, and Planning (2019) — 151 citations
- Pommerman: A Multi-Agent Playground (2018) — 90 citations
- Procedural Content Generation via Machine Learning (PCGML) (2017) — 463 citations
- Measuring Intelligence through Games (2011) — 59 citations
- The 2009 Simulated Car Racing Championship (2010) — 103 citations
- New And Surprising Ways to Be Mean (2018) — 16 citations
- The 2009 Mario AI Competition (2010) — 175 citations
- Super mario evolution (2009) — 117 citations
- Increasing generality in machine learning through procedural content generation (2019) — 149 citations
- Towards automatic personalised content creation for racing games (2007) — 315 citations
- Autoencoder-augmented neuroevolution for visual doom playing (2017) — 63 citations
- Search-Based Procedural Content Generation: A Taxonomy and Survey (2011) — 779 citations
- Experience-Driven Procedural Content Generation (2011) — 517 citations
- The 2014 General Video Game Playing Competition (2016) — 209 citations
- Choose Your Weapon: Survival Strategies for Depressed AI Academics (2023) — 18 citations
- Diverse Agents for Ad-Hoc Cooperation in Hanabi (2019) — 50 citations
- Evolving Agents for the Hanabi 2018 CIG Competition (2018) — 26 citations
- DeepTingle (2017) — 32 citations