Human-Like Understanding of Two-Line Figures. - Steven Stenberg Hansen; David S. Touretzky (FLAIRS, 2011)

Two Plus Three Is Five: Discovering Efficient Addition Strategies without Metacognition. - Steven Stenberg Hansen; Cameron R. L. McKenzie; James L. McClelland (CogSci, 2014)

Tutorial Workshop on Contemporary Deep Neural Network Models. - James L. McClelland; Steven Stenberg Hansen; Andrew M. Saxe (CogSci, 2016)

N400 amplitudes reflect change in a probabilistic representation of meaning: Evidence from a connectionist model. - Milena Rabovsky; Steven Stenberg Hansen; James L. McClelland (CogSci, 2016)

Neural responses decrease while performance increases with practice: A neural network model. - Milena Rabovsky; Steven Stenberg Hansen; James L. McClelland (CogSci, 2017)

Long Timescale Credit Assignment in NeuralNetworks with External Memory. - Steven Stenberg Hansen (CoRR, 2017)

Minimally Naturalistic Artificial Intelligence. - Steven Stenberg Hansen (CoRR, 2017)

Deep Episodic Value Iteration for Model-based Meta-Reinforcement Learning. - Steven Stenberg Hansen (CoRR, 2017)

Fast deep reinforcement learning using online adjustments from the past. - Steven Hansen 001; Alexander Pritzel; Pablo Sprechmann; André Barreto 001; Charles Blundell (NeurIPS, 2018)

Unsupervised Control Through Non-Parametric Discriminative Rewards. - David Warde-Farley; Tom Van de Wiele; Tejas D. Kulkarni; Catalin Ionescu; Steven Hansen 001; Volodymyr Mnih (ICLR (Poster), 2019)

Generalization of Reinforcement Learners with Working and Episodic Memory. - Meire Fortunato; Melissa Tan; Ryan Faulkner 001; Steven Hansen 001; Adrià Puigdomènech Badia; Gavin Buttimore; Charlie Deck; Joel Z. Leibo; Charles Blundell (NeurIPS, 2019)

Fast Task Inference with Variational Intrinsic Successor Features. - Steven Hansen 001; Will Dabney; André Barreto 001; David Warde-Farley; Tom Van de Wiele; Volodymyr Mnih (ICLR, 2020)

Relative Variational Intrinsic Control. - Kate Baumli; David Warde-Farley; Steven Hansen 001; Volodymyr Mnih (AAAI, 2021)

Entropic Desired Dynamics for Intrinsic Control. - Steven Hansen 001; Guillaume Desjardins; Kate Baumli; David Warde-Farley; Nicolas Heess; Simon Osindero; Volodymyr Mnih (NeurIPS, 2021)

Coverage as a Principle for Discovering Transferable Behavior in Reinforcement Learning. - Víctor Campos 001; Pablo Sprechmann; Steven Hansen 001; André Barreto 001; Steven Kapturowski; Alex Vitvitskyi; Adrià Puigdomènech Badia; Charles Blundell (CoRR, 2021)

Wasserstein Distance Maximizing Intrinsic Control. - Ishan Durugkar; Steven Hansen 001; Stephen Spencer; Volodymyr Mnih (CoRR, 2021)

Learning more skills through optimistic exploration. - DJ Strouse; Kate Baumli; David Warde-Farley; Volodymyr Mnih; Steven Stenberg Hansen (ICLR, 2022)

Uniqueness and Complexity of Inverse MDP Models. - Marcus Hutter; Steven Hansen 001 (CoRR, 2022)

In-context Reinforcement Learning with Algorithm Distillation. - Michael Laskin; Luyu Wang; Junhyuk Oh; Emilio Parisotto; Stephen Spencer; Richie Steigerwald; DJ Strouse; Steven Stenberg Hansen; Angelos Filos; Ethan Brooks; Maxime Gazeau; Himanshu Sahni; et al. (ICLR, 2023)

Agency Is Frame-Dependent. - David Abel; André Barreto 001; Michael Bowling; Will Dabney; Shi Dong; Steven Hansen 001; Anna Harutyunyan; Khimya Khetarpal; Clare Lyle; Razvan Pascanu; Georgios Piliouras; Doina Precup; et al. (CoRR, 2025)

Plasticity as the Mirror of Empowerment. - David Abel; Michael Bowling; André Barreto 001; Will Dabney; Shi Dong; Steven Hansen 001; Anna Harutyunyan; Khimya Khetarpal; Clare Lyle; Razvan Pascanu; Georgios Piliouras; Doina Precup; et al. (CoRR, 2025)