dimitra-maoutsa

CompressionVAE

General-purpose dimensionality reduction and manifold learning tool based on Variational Autoencoder, implemented in TensorFlow.

Connectivity_from_event_timing_patterns

Model-free method for inferring synaptic interactions from spike train recordings.

data-science-course

DeterministicParticleFlowControl

Repository for Deterministic Particle Flow Control framework

difolio

Trial website

Geometric-path-augmentation-for-SDEs

Repository for inference method for stochastic processes through geometric path augmentation

inferring-synaptic-interactions-and-transmission-delays

lecture-network-dynamics-and-complex-systems

Lecture material for part (4/12) of the lecture **Network Dynamics & Complex Systems - Theoretical and Computational Tools** given during winter semester 2016/17 at Georg-August-Universität Göttingen

odes_for_sdes

Deterministic particle dynamics for simulating Fokker-Planck probability flows

Perturbing_oscillatory_spiking_neural_networks

old code

dimitra-maoutsa/odes_for_sdes

Deterministic particle dynamics for simulating Fokker-Planck probability flows

dimitra-maoutsa/DeterministicParticleFlowControl

Repository for Deterministic Particle Flow Control framework

dimitra-maoutsa/Geometric-path-augmentation-for-SDEs

Repository for inference method for stochastic processes through geometric path augmentation

dimitra-maoutsa/lecture-network-dynamics-and-complex-systems

Lecture material for part (4/12) of the lecture **Network Dynamics & Complex Systems - Theoretical and Computational Tools** given during winter semester 2016/17 at Georg-August-Universität Göttingen

dimitra-maoutsa/Connectivity_from_event_timing_patterns

Model-free method for inferring synaptic interactions from spike train recordings.

dimitra-maoutsa/Perturbing_oscillatory_spiking_neural_networks

old code

dimitra-maoutsa/inferring-synaptic-interactions-and-transmission-delays

dimitra-maoutsa/CompressionVAE

General-purpose dimensionality reduction and manifold learning tool based on Variational Autoencoder, implemented in TensorFlow.

dimitra-maoutsa/difolio

Trial website

dimitra-maoutsa/dimitra-maoutsa

dimitra-maoutsa/geomloss

Geometric loss functions between point clouds, images and volumes

dimitra-maoutsa/GRAE

Geometry Regularized Autoencoders (GRAE) for large-scale visualization and manifold learning

dimitra-maoutsa/LSGM

The Official PyTorch Implementation of "LSGM: Score-based Generative Modeling in Latent Space" (NeurIPS 2021)

dimitra-maoutsa/M-Dims-Blog

Blog of M Dims >>> https://dimitra-maoutsa.github.io/M-Dims-Blog/

dimitra-maoutsa/neuralflow

The framework for inferring Langevin dynamics from spike data

dimitra-maoutsa/neurodiffeq

A library for solving differential equations using neural networks based on PyTorch, used by multiple research groups around the world, including at Harvard IACS.

dimitra-maoutsa/neurodiffeq-playground

Playground repo for solving differential equations using the neurodiffeq package

dimitra-maoutsa/PINA

Physics-Informed Neural networks for Advanced modeling

dimitra-maoutsa/Probability-flow-dynamics-for-constrained-stochastic-nonlinear-systems

Detailed explanation of the Deterministic Particle Control method briefly outlined in [upcoming paper] + code

dimitra-maoutsa/pylustrator

Visualisations of data are at the core of every publication of scientific research results. They have to be as clear as possible to facilitate the communication of research. As data can have different formats and shapes, the visualisations often have to be adapted to reflect the data as well as possible. We developed Pylustrator, an interface to directly edit python generated matplotlib graphs to finalize them for publication. Therefore, subplots can be resized and dragged around by the mouse, text and annotations can be added. The changes can be saved to the initial plot file as python code.

dimitra-maoutsa/pysph

A framework for Smoothed Particle Hydrodynamics in Python

dimitra-maoutsa/python_register_color_palettes

For later reference - to avoid searching

dimitra-maoutsa/random_util_funcs

mostly for data analysis

dimitra-maoutsa/reaction-diffusion-playground

Interactive reaction-diffusion simulation with organic patterns and behaviors that emerge from the interactions of two chemicals mixed together.

dimitra-maoutsa/recurrent-whisperer

Python baseclass for training recurrent neural networks in Tensorflow

dimitra-maoutsa/scikit-learn

scikit-learn: machine learning in Python

dimitra-maoutsa/score_function_estimators

collection of the score estimators I use

dimitra-maoutsa/some_random_notebooks

dimitra-maoutsa/torchdyn

A PyTorch library entirely dedicated to neural differential equations, implicit models and related numerical methods.

dimitra-maoutsa/UnderdampedLangevinInference

Python implementation of Underdamped Langevin Inference, a method to infer the dynamical equation of underdamped stochastic systems from discrete noisy time series.