David Ha - RankMe

67 papers A* 6A 4B 1C 4Journal 37Unranked 15

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Digital Red Queen: Adversarial Program Evolution in Core War with LLMs. CoRR Akarsh Kumar, Ryan Bahlous-Boldi, Prafull Sharma, Phillip Isola, Sebastian Risi, Yujin Tang, David Ha
2025	J	`jnl`	EDINET-Bench: Evaluating LLMs on Complex Financial Tasks using Japanese Financial Statements. CoRR Issa Sugiura, Takashi Ishida, Taro Makino, Chieko Tazuke, Takanori Nakagawa, Kosuke Nakago, David Ha
2025	—	`conf`	Evolution of Neural Networks. GECCO Companion Risto Miikkulainen, Sebastian Risi, David Ha, Yujin Tang
2025	J	`jnl`	Evolutionary optimization of model merging recipes. Nat. Mac. Intell. Takuya Akiba, Makoto Shing, Yujin Tang, Qi Sun, David Ha
2025	J	`jnl`	The AI Scientist-v2: Workshop-Level Automated Scientific Discovery via Agentic Tree Search. CoRR Yutaro Yamada, Robert Tjarko Lange, Cong Lu, Shengran Hu, Chris Lu, Jakob N. Foerster, Jeff Clune, David Ha
2025	J	`jnl`	Towards Robust Agentic CUDA Kernel Benchmarking, Verification, and Optimization. CoRR Robert Tjarko Lange, Qi Sun, Aaditya Prasad, Maxence Faldor, Yujin Tang, David Ha
2024	J	`jnl`	Automating the Search for Artificial Life with Foundation Models. CoRR Akarsh Kumar, Chris Lu, Louis Kirsch, Yujin Tang, Kenneth O. Stanley, Phillip Isola, David Ha
2024	J	`jnl`	Evolutionary Optimization of Model Merging Recipes. CoRR Takuya Akiba, Makoto Shing, Yujin Tang, Qi Sun, David Ha
2024	J	`jnl`	Learning to Generalize With Object-Centric Agents in the Open World Survival Game Crafter. IEEE Trans. Games Aleksandar Stanic, Yujin Tang, David Ha, Jürgen Schmidhuber
2024	J	`jnl`	The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery. CoRR Chris Lu, Cong Lu, Robert Tjarko Lange, Jakob N. Foerster, Jeff Clune, David Ha
2022	J	`jnl`	EvoJAX: Hardware-Accelerated Neuroevolution. CoRR Yujin Tang, Yingtao Tian, David Ha
2022	—	`conf`	EvoJAX: hardware-accelerated neuroevolution. GECCO Companion Yujin Tang, Yingtao Tian, David Ha
2022	J	`jnl`	Evolving Modular Soft Robots without Explicit Inter-Module Communication using Local Self-Attention. CoRR Federico Pigozzi, Yujin Tang, Eric Medvet, David Ha
2022	A	`conf`	Evolving modular soft robots without explicit inter-module communication using local self-attention. GECCO Federico Pigozzi, Yujin Tang, Eric Medvet, David Ha
2022	J	`jnl`	Learning to Generalize with Object-centric Agents in the Open World Survival Game Crafter. CoRR Aleksandar Stanic, Yujin Tang, David Ha, Jürgen Schmidhuber
2022	C	`conf`	Modern Evolution Strategies for Creativity: Fitting Concrete Images and Abstract Concepts. EvoMUSART Yingtao Tian, David Ha
2022	C	`conf`	Simultaneous Multiple-Prompt Guided Generation Using Differentiable Optimal Transport. ICCC Yingtao Tian, Marco Cuturi, David Ha
2022	J	`jnl`	Simultaneous Multiple-Prompt Guided Generation Using Differentiable Optimal Transport. CoRR Yingtao Tian, Marco Cuturi, David Ha
2021	J	`jnl`	An Improved Boundary Uncertainty-Based Estimation for Classifier Evaluation. J. Signal Process. Syst. David Ha, Shigeru Katagiri, Hideyuki Watanabe, Miho Ohsaki
2021	J	`jnl`	Collective Intelligence for Deep Learning: A Survey of Recent Developments. CoRR David Ha, Yujin Tang
2021	J	`jnl`	Modern Evolution Strategies for Creativity: Fitting Concrete Images and Abstract Concepts. CoRR Yingtao Tian, David Ha
2021	J	`jnl`	Sketch-based Creativity Support Tools using Deep Learning. CoRR Forrest Huang, Eldon Schoop, David Ha, Jeffrey Nichols, John F. Canny
2021	A*	`conf`	The Sensory Neuron as a Transformer: Permutation-Invariant Neural Networks for Reinforcement Learning. NeurIPS Yujin Tang, David Ha
2021	J	`jnl`	The Sensory Neuron as a Transformer: Permutation-Invariant Neural Networks for Reinforcement Learning. CoRR Yujin Tang, David Ha
2021	C	`conf`	World Models and Attention for Reinforcement Learning. ALIFE David Ha
2020	J	`jnl`	A Practical Method Based on Bayes Boundary-Ness for Optimal Classifier Parameter Status Selection. J. Signal Process. Syst. David Ha, Yuya Tomotoshi, Masahiro Senda, Hideyuki Watanabe, Shigeru Katagiri, Miho Ohsaki
2020	C	`conf`	Finding Game Levels with the Right Difficulty in a Few Trials through Intelligent Trial-and-Error. CoG Miguel González Duque, Rasmus Berg Palm, David Ha, Sebastian Risi
2020	J	`jnl`	Finding Game Levels with the Right Difficulty in a Few Trials through Intelligent Trial-and-Error. CoRR Miguel González Duque, Rasmus Berg Palm, David Ha, Sebastian Risi
2020	—	`conf`	Neuroevolution for deep reinforcement learning problems. GECCO Companion David Ha
2020	J	`jnl`	Neuroevolution of Self-Interpretable Agents. CoRR Yujin Tang, Duong Nguyen, David Ha
2020	A	`conf`	Neuroevolution of self-interpretable agents. GECCO Yujin Tang, Duong Nguyen, David Ha
2020	J	`jnl`	Scones: Towards Conversational Authoring of Sketches. CoRR Forrest Huang, Eldon Schoop, David Ha, John F. Canny
2020	A	`conf`	Scones: towards conversational authoring of sketches. IUI Forrest Huang, Eldon Schoop, David Ha, John F. Canny
2020	A	`conf`	SketchTransfer: A Challenging New Task for Exploring Detail-Invariance and the Abstractions Learned by Deep Networks. WACV Alex Lamb, Sherjil Ozair, Vikas Verma, David Ha
2019	A*	`conf`	A Learned Representation for Scalable Vector Graphics. ICCV Raphael Gontijo Lopes, David Ha, Douglas Eck, Jonathon Shlens
2019	—	`conf`	A Learned Representation for Scalable Vector Graphics. DGS@ICLR Raphael Gontijo Lopes, David Ha, Douglas Eck, Jonathon Shlens
2019	J	`jnl`	A Learned Representation for Scalable Vector Graphics. CoRR Raphael Gontijo Lopes, David Ha, Douglas Eck, Jonathon Shlens
2019	A*	`conf`	Learning Latent Dynamics for Planning from Pixels. ICML Danijar Hafner, Timothy P. Lillicrap, Ian Fischer, Ruben Villegas, David Ha, Honglak Lee, James Davidson
2019	A*	`conf`	Learning to Predict Without Looking Ahead: World Models Without Forward Prediction. NeurIPS C. Daniel Freeman, David Ha, Luke Metz
2019	J	`jnl`	Learning to Predict Without Looking Ahead: World Models Without Forward Prediction. CoRR C. Daniel Freeman, Luke Metz, David Ha
2019	—	`conf`	Maximum Bayes Boundary-Ness Training For Pattern Classification. SPML Masahiro Senda, David Ha, Hideyuki Watanabe, Shigeru Katagiri, Miho Ohsaki
2019	—	`conf`	Neuroevolution for deep reinforcement learning problems. GECCO (Companion) David Ha
2019	—	`conf`	Optimal Classifier Parameter Status Selection Based on Bayes Boundary-ness for Multi-ProtoType and Multi-Layer Perceptron Classifiers. IUKM Yuya Tomotoshi, David Ha, Emilie Delattre, Hideyuki Watanabe, Xugang Lu, Shigeru Katagiri, Miho Ohsaki
2019	J	`jnl`	Reinforcement Learning for Improving Agent Design. Artif. Life David Ha
2019	J	`jnl`	SketchTransfer: A Challenging New Task for Exploring Detail-Invariance and the Abstractions Learned by Deep Networks. CoRR Alex Lamb, Sherjil Ozair, Vikas Verma, David Ha
2019	A*	`conf`	Weight Agnostic Neural Networks. NeurIPS Adam Gaier, David Ha
2019	J	`jnl`	Weight Agnostic Neural Networks. CoRR Adam Gaier, David Ha
2019	B	`conf`	collabdraw: An Environment for Collaborative Sketching with an Artificial Agent. Creativity & Cognition Judith E. Fan, Monica Dinculescu, David Ha
2018	—	`conf`	A Neural Representation of Sketch Drawings. ICLR (Poster) David Ha, Douglas Eck
2018	J	`jnl`	Deep Learning for Classical Japanese Literature. CoRR Tarin Clanuwat, Mikel Bober-Irizar, Asanobu Kitamoto, Alex Lamb, Kazuaki Yamamoto, David Ha
2018	J	`jnl`	Learning Latent Dynamics for Planning from Pixels. CoRR Danijar Hafner, Timothy P. Lillicrap, Ian Fischer, Ruben Villegas, David Ha, Honglak Lee, James Davidson
2018	—	`conf`	Learning via Social Awareness: Improving a Deep Generative Sketching Model with Facial Feedback. AffComp@IJCAI Natasha Jaques, Jennifer McCleary, Jesse H. Engel, David Ha, Fred Bertsch, Douglas Eck, Rosalind W. Picard
2018	—	`conf`	Learning via social awareness: improving sketch representations with facial feedback. ICLR (Workshop) Natasha Jaques, Jesse H. Engel, David Ha, Fred Bertsch, Rosalind W. Picard, Douglas Eck
2018	J	`jnl`	Learning via social awareness: improving sketch representations with facial feedback. CoRR Natasha Jaques, Jesse H. Engel, David Ha, Fred Bertsch, Rosalind W. Picard, Douglas Eck
2018	—	`conf`	Neuroevolution for deep reinforcement learning problems. GECCO (Companion) David Ha
2018	—	`conf`	Optimal Classifier Model Status Selection using Bayes boundary uncertainty. MLSP David Ha, Emilie Delattre, Yuya Tomotoshi, Masahiro Senda, Hideyuki Watanabe, Shigeru Katagiri, Miho Ohsaki
2018	—	`conf`	Optimality Analysis of Boundary-Uncertainty-Based Classifier Model Parameter Status Selection Method. SPML David Ha, Hideyuki Watanabe, Yuya Tomotoshi, Emilie Delattre, Shigeru Katagiri
2018	—	`conf`	Pommerman: A Multi-Agent Playground. AIIDE Workshops Cinjon Resnick, Wes Eldridge, David Ha, Denny Britz, Jakob N. Foerster, Julian Togelius, Kyunghyun Cho, Joan Bruna
2018	J	`jnl`	Pommerman: A Multi-Agent Playground. CoRR Cinjon Resnick, Wes Eldridge, David Ha, Denny Britz, Jakob N. Foerster, Julian Togelius, Kyunghyun Cho, Joan Bruna
2018	A*	`conf`	Recurrent World Models Facilitate Policy Evolution. NeurIPS David Ha, Jürgen Schmidhuber
2018	J	`jnl`	Recurrent World Models Facilitate Policy Evolution. CoRR David Ha, Jürgen Schmidhuber
2018	J	`jnl`	Reinforcement Learning for Improving Agent Design. CoRR David Ha
2018	J	`jnl`	World Models. CoRR David Ha, Jürgen Schmidhuber
2017	J	`jnl`	A Neural Representation of Sketch Drawings. CoRR David Ha, Douglas Eck
2017	—	`conf`	HyperNetworks. ICLR (Poster) David Ha, Andrew M. Dai, Quoc V. Le
2017	J	`jnl`	PathNet: Evolution Channels Gradient Descent in Super Neural Networks. CoRR Chrisantha Fernando, Dylan Banarse, Charles Blundell, Yori Zwols, David Ha, Andrei A. Rusu, Alexander Pritzel, Daan Wierstra
2016	J	`jnl`	HyperNetworks. CoRR David Ha, Andrew M. Dai, Quoc V. Le