T. Anderson Keller

Affiliations:
  • The Kempner Institute for the Study of Natural and Artificial Intelligence at Harvard University, Cambridge, USA
  • University of Amsterdam, Amsterdam, The Netherlands (former)


According to our database1, T. Anderson Keller authored at least 18 papers between 2021 and 2026.

Collaborative distances:

Timeline

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Bibliography

2026
Spontaneous symmetry breaking and Goldstone modes for deep information propagation.
CoRR, May, 2026

Unsupervised Representation Learning From Sparse Transformation Analysis.
IEEE Trans. Pattern Anal. Mach. Intell., April, 2026

2025
Kuramoto Orientation Diffusion Models.
CoRR, September, 2025

Langevin Flows for Modeling Neural Latent Dynamics.
CoRR, July, 2025

Bridging Expressivity and Scalability with Adaptive Unitary SSMs.
CoRR, July, 2025

Origins of Creativity in Attention-Based Diffusion Models.
CoRR, June, 2025

Traveling Waves Integrate Spatial Information Through Time.
CoRR, February, 2025

2024
Learning Artistic Signatures: Symmetry Discovery and Style Transfer.
CoRR, 2024

A Spacetime Perspective on Dynamical Computation in Neural Information Processing Systems.
CoRR, 2024

Traveling Waves Encode The Recent Past and Enhance Sequence Learning.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023
Image segmentation with traveling waves in an exactly solvable recurrent neural network.
CoRR, 2023

Flow Factorized Representation Learning.
CoRR, 2023

Latent Traversals in Generative Models as Potential Flows.
Proceedings of the International Conference on Machine Learning, 2023

Neural Wave Machines: Learning Spatiotemporally Structured Representations with Locally Coupled Oscillatory Recurrent Neural Networks.
Proceedings of the International Conference on Machine Learning, 2023

2021
Modeling Category-Selective Cortical Regions with Topographic Variational Autoencoders.
CoRR, 2021

Topographic VAEs learn Equivariant Capsules.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Self Normalizing Flows.
Proceedings of the 38th International Conference on Machine Learning, 2021

Predictive Coding with Topographic Variational Autoencoders.
Proceedings of the IEEE/CVF International Conference on Computer Vision Workshops, 2021


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