Publications

(2022). Efficient spatio-temporal feature clustering for large event-based datasets. Neuromorphic Computing and Engineering.

DOI

(2022). Dissecting Self-Supervised Learning Methods for Surgical Computer Vision. Pre-Print.

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(2022). A sampling-based approach for efficient clustering in large datasets. In CVPR 2022.

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(2019). ProSper - A Python Library for Probabilistic Sparse Coding with Non-Standard Priors and Superpositions. A Python Library for Probabilistic Sparse Coding with Non-Standard Priors and Superpositions.

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(2018). Kymatio: Scattering Transforms in Python. JMLR.

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(2018). Truncated Variational Sampling for ‘Black Box’ Optimization of Generative Models. In LVA/ICA.

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(2018). Solid harmonic wavelet scattering for predictions of molecule properties. In JCP.

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(2017). Solid Harmonic Wavelet Scattering: Predicting Quantum Molecular Energy from Invariant Descriptors of 3D Electronic Densities. In NIPS.

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(2017). Discrete Sparse Coding. In NeCo.

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(2016). Probabilistic Models for Invariant Representations and Transformations. Doctoral Dissertation.

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(2013). Learning invariant features by harnessing the aperture problem. In ICML 2013.

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(2012). Ternary Sparse Coding. LVA/ICA.

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(2011). Discrete Symmetric Priors for Sparse Coding. In Bernstein Conference.

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