Grant, Erin

11 publications

TMLR 2025 Getting Aligned on Representational Alignment Ilia Sucholutsky, Lukas Muttenthaler, Adrian Weller, Andi Peng, Andreea Bobu, Been Kim, Bradley C. Love, Christopher J Cueva, Erin Grant, Iris Groen, Jascha Achterberg, Joshua B. Tenenbaum, Katherine M. Collins, Katherine Hermann, Kerem Oktar, Klaus Greff, Martin N Hebart, Nathan Cloos, Nikolaus Kriegeskorte, Nori Jacoby, Qiuyi Zhang, Raja Marjieh, Robert Geirhos, Sherol Chen, Simon Kornblith, Sunayana Rane, Talia Konkle, Thomas O'Connell, Thomas Unterthiner, Andrew Kyle Lampinen, Klaus Robert Muller, Mariya Toneva, Thomas L. Griffiths
ICML 2025 Not All Solutions Are Created Equal: An Analytical Dissociation of Functional and Representational Similarity in Deep Linear Neural Networks Lukas Braun, Erin Grant, Andrew M Saxe
NeurIPS 2024 Nonlinear Dynamics of Localization in Neural Receptive Fields Leon Lufkin, Andrew Saxe, Erin Grant
UAI 2023 Gaussian Process Surrogate Models for Neural Networks Michael Y. Li, Erin Grant, Thomas L. Griffiths
NeurIPS 2023 The Transient Nature of Emergent In-Context Learning in Transformers Aaditya Singh, Stephanie Chan, Ted Moskovitz, Erin Grant, Andrew Saxe, Felix Hill
ICML 2022 Distinguishing Rule and Exemplar-Based Generalization in Learning Systems Ishita Dasgupta, Erin Grant, Tom Griffiths
ICMLW 2022 Predicting Generalization with Degrees of Freedom in Neural Networks Erin Grant, Yan Wu
NeurIPSW 2021 Meta-Learning Inductive Biases of Learning Systems with Gaussian Processes Michael Y. Li, Erin Grant, Thomas L. Griffiths
NeurIPS 2021 Passive Attention in Artificial Neural Networks Predicts Human Visual Selectivity Thomas Langlois, Haicheng Zhao, Erin Grant, Ishita Dasgupta, Tom Griffiths, Nori Jacoby
NeurIPS 2019 Reconciling Meta-Learning and Continual Learning with Online Mixtures of Tasks Ghassen Jerfel, Erin Grant, Tom Griffiths, Katherine A. Heller
ICLR 2018 Recasting Gradient-Based Meta-Learning as Hierarchical Bayes Erin Grant, Chelsea Finn, Sergey Levine, Trevor Darrell, Thomas Griffiths