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Oct 1, 2020 - Python
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jax
Here are 56 public repositories matching this topic...
Trax — Deep Learning with Clear Code and Speed
machine-learning
reinforcement-learning
deep-learning
numpy
deep-reinforcement-learning
transformer
jax
python
nlp
machine-learning
natural-language-processing
ai
deep-learning
mxnet
functional-programming
tensorflow
pytorch
artificial-intelligence
spacy
machine-learning-library
type-checking
jax
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Oct 1, 2020 - Python
A Python toolbox to create adversarial examples that fool neural networks in PyTorch, TensorFlow, and JAX
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Sep 27, 2020 - Python
Fast and Easy Infinite Neural Networks in Python
kernel
neural-networks
gradient-descent
bayesian-inference
gaussian-processes
bayesian-networks
deep-networks
gradient-flow
jax
infinite-networks
training-dynamics
neural-tangents
kernel-computation
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Oct 1, 2020 - Jupyter Notebook
Official repository for the "Big Transfer (BiT): General Visual Representation Learning" paper.
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Sep 25, 2020 - Python
JAX-based neural network library
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Sep 17, 2020 - Python
PyTorch, TensorFlow, JAX and NumPy — all of them natively using the same code
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Sep 26, 2020 - Python
Fast Differentiable Sorting and Ranking
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Jul 28, 2020 - Python
Concise deep learning with JAX
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Aug 18, 2020 - Python
lukasheinrich
commented
Jul 29, 2020
right now we use "twice_nll" as a fit objective and in the test statistic a simple diffence
twice_nll_constrfit - twice_nll_globalfit
but rather we should just to a NLL fit and in the test stat do
2*(nll_constrfit - nll_globalfit)
this will require updating some test reference numbers in the tests
A suite of benchmarks to test the sequential CPU and GPU performance of most popular high-performance libraries for Python.
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Aug 3, 2020 - Python
Documentation:
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Sep 28, 2020 - Python
Code for the paper "Learning Differential Equations that are Easy to Solve"
machine-learning
deep-neural-networks
deep-learning
ode
dynamical-systems
differential-equations
numerical-integration
ode-solver
jax
neural-ode
neural-differential-equations
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Jul 18, 2020 - Python
stuhlmueller
commented
Jun 7, 2020
Pytorch and Jax code for the Madam optimiser.
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Jul 19, 2020 - Jupyter Notebook
umangjpatel
commented
Jan 17, 2020
Description
Update README and add experiments.
Solution
Create experiments or examples package to work
Differentiable interface to FEniCS for JAX using dolfin-adjoint/pyadjoint
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Aug 14, 2020 - Jupyter Notebook
Google AI Princeton control framework
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Aug 12, 2020 - Jupyter Notebook
Collection of useful omnifocus applescripts
productivity
automation
applescript
extensions
icons
omnifocus
omni
jax
omnifocus-library
omnifocus3
omnigroup
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Jan 24, 2019 - AppleScript
JAX implementations of core Deep RL algorithms
reinforcement-learning
deep-learning
deep-reinforcement-learning
flax
deepmind
sac
actor-critic
maximum-a-posteriori-estimation
mujoco
jax
td3
soft-actor-critic
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Sep 25, 2020 - Python
Differentiable interface to FEniCS for JAX
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Apr 17, 2020 - Python
A JAX Implementation of the Twin Delayed DDPG Algorithm
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Mar 12, 2020 - Jupyter Notebook
A Python 3 toolbox for neural receptive field estimation using splines and Gaussian priors.
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Sep 30, 2020 - Python
JAX implementation of Graph Attention Networks
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Apr 26, 2020 - Python
Graph Convolutional Networks in JAX
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May 8, 2020 - Python
small experiments with agents learning atari games, implemented in jax/numpy
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Mar 16, 2019 - Python
minimal C-interpreter to play with. for learning purpose
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Jan 9, 2018 - C
Samplers from the paper "Stochastic Gradient MCMC with Repulsive Forces"
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Feb 3, 2020 - Jupyter Notebook
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Per a question asked by a user in the forum, it would be nice to have a tutorial/example for this type of regression. I searched for some examples available and found some nice ones below.