A package related to building quasi-fibration symmetries

Last update: Dec 01, 2021

Related tags

Deep Learning qf

Overview

qf

A package related to building quasi-fibration symmetries.

If you'd like to learn more about how it works, see the brief explanation and References below.

Brought to you by Paolo Boldi ([email protected]).

Read the full documentation for more information.

Installation
Mathematical background
Jupyter Notebook Tutorial (see also the Installation section)
Scripts

References

Boldi, Paolo, and Sebastiano Vigna. Fibrations of graphs. Discrete Mathematics 243.1-3 (2002): 21-66.
Leifer, Ian, et al. Circuits with broken fibration symmetries perform core logic computations in biological networks. PLoS computational biology 16.6 (2020): e1007776.
Golubitsky, Martin, and Ian Stewart. Nonlinear dynamics of networks: the groupoid formalism. Bulletin of the american mathematical society 43.3 (2006): 305-364.

Owner

Paolo Boldi

GitHub Repository

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A package related to building quasi-fibration symmetries

Related tags

Overview

qf

References

Owner

Paolo Boldi

Towards Rolling Shutter Correction and Deblurring in Dynamic Scenes (CVPR2021)

PyTorch - Python + Nim

Code for NeurIPS2021 submission "A Surrogate Objective Framework for Prediction+Programming with Soft Constraints"

Implementation of the paper "Self-Promoted Prototype Refinement for Few-Shot Class-Incremental Learning"

Rasterize with the least efforts for researchers.

Code for our ALiBi method for transformer language models.

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Implementation of Convolutional LSTM in PyTorch.

Pytorch implementation of "MOSNet: Deep Learning based Objective Assessment for Voice Conversion"

Source code for our Paper "Learning in High-Dimensional Feature Spaces Using ANOVA-Based Matrix-Vector Multiplication"

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