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Summary of the DREAM8 Parameter Estimation Challenge: Toward Parameter Identification for Whole-Cell Models, , , , , , , , , and 6 other author(s). PLoS Comput Biol, 11 (5): e1004096+ (May 28, 2015)Explaining heterogeneity in medial entorhinal cortex with task-driven neural networks., , , , , , , , , and 2 other author(s). NeurIPS, page 12167-12179. (2021)Distinguishing discrete and continuous behavioral variability using warped autoregressive HMMs., , , , , , , , and . NeurIPS, (2022)Universality and individuality in neural dynamics across large populations of recurrent networks., , , , and . NeurIPS, page 15603-15615. (2019)Generalized Shape Metrics on Neural Representations., , , and . NeurIPS, page 4738-4750. (2021)Point process models for sequence detection in high-dimensional neural spike trains., , , and . NeurIPS, (2020)Estimating Shape Distances on Neural Representations with Limited Samples., , , and . CoRR, (2023)Soft Matching Distance: A metric on neural representations that captures single-neuron tuning., and . UniReps, volume 243 of Proceedings of Machine Learning Research, page 326-341. PMLR, (2023)Representational Dissimilarity Metric Spaces for Stochastic Neural Networks., , , , , and . ICLR, OpenReview.net, (2023)Reverse engineering recurrent networks for sentiment classification reveals line attractor dynamics., , , , and . NeurIPS, page 15670-15679. (2019)