Cognitive and action control for goal-directed reaching in a humanoid robot. - Jerald D. Kralik; Daniel B. C. Muldrew; Divya Gunasekaran; Richard D. Lange (ROBIO, 2017)

A probabilistic population code based on neural samples. - Sabyasachi Shivkumar; Richard D. Lange; Ankani Chattoraj; Ralf M. Haefner (NeurIPS, 2018)

A confirmation bias in perceptual decision-making due to hierarchical approximate inference. - Richard D. Lange; Ankani Chattoraj; Jeffrey M. Beck; Jacob L. Yates; Ralf M. Haefner (PLoS Comput. Biol., 2021)

Interpolating between sampling and variational inference with infinite stochastic mixtures. - Richard D. Lange; Ari S. Benjamin; Ralf M. Haefner; Xaq Pitkow (UAI, 2022)

Neural Networks as Paths through the Space of Representations. - Richard D. Lange; Jordan Matelsky; Xinyue Wang; Devin Kwok; David S. Rolnick; Konrad P. Kording (CoRR, 2022)

Task-induced neural covariability as a signature of approximate Bayesian learning and inference. - Richard D. Lange; Ralf M. Haefner (PLoS Comput. Biol., 2022)

Clustering units in neural networks: upstream vs downstream information. - Richard D. Lange; David Rolnick; Konrad P. Kording (Trans. Mach. Learn. Res., 2022)

Deep Networks as Paths on the Manifold of Neural Representations. - Richard D. Lange; Devin Kwok; Jordan Kyle Matelsky; Xinyue Wang; David Rolnick; Konrad P. Kording (TAG-ML, 2023)

A large language model-assisted education tool to provide feedback on open-ended responses. - Jordan K. Matelsky; Felipe Parodi; Tony Liu 004; Richard D. Lange; Konrad P. Kording (CoRR, 2023)

Causality in the human niche: lessons for machine learning. - Richard D. Lange; Konrad P. Kording (CoRR, 2025)