snavalm's Stars
tensorflow/models
Models and examples built with TensorFlow
BVLC/caffe
Caffe: a fast open framework for deep learning.
pytorch/examples
A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.
dennybritz/reinforcement-learning
Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.
microsoft/computervision-recipes
Best Practices, code samples, and documentation for Computer Vision.
aikorea/awesome-rl
Reinforcement learning resources curated
facebookresearch/pytorch3d
PyTorch3D is FAIR's library of reusable components for deep learning with 3D data
eriklindernoren/PyTorch-YOLOv3
Minimal PyTorch implementation of YOLOv3
yandexdataschool/Practical_RL
A course in reinforcement learning in the wild
udacity/deep-reinforcement-learning
Repo for the Deep Reinforcement Learning Nanodegree program
hoya012/awesome-anomaly-detection
A curated list of awesome anomaly detection resources
pmorissette/ffn
ffn - a financial function library for Python
GoogleCloudPlatform/cloudml-samples
Cloud ML Engine repo. Please visit the new Vertex AI samples repo at https://github.com/GoogleCloudPlatform/vertex-ai-samples
facebookresearch/DeepSDF
Learning Continuous Signed Distance Functions for Shape Representation
ranahanocka/point2mesh
Reconstruct Watertight Meshes from Point Clouds [SIGGRAPH 2020]
rll/deepul
dingmaotu/mql-zmq
ZMQ binding for the MQL language (both 32bit MT4 and 64bit MT5)
atgambardella/pytorch-es
Evolution Strategies in PyTorch
enochkan/awesome-gans-and-deepfakes
A curated list of GAN & Deepfake papers and repositories.
amymcgovern/pyparrot
Python interface for Parrot Drones
tbmoon/facenet
FaceNet for face recognition using pytorch
MIC-DKFZ/mood
Repository for the Medical Out-of-Distribution Analysis Challenge.
MIC-DKFZ/vae-anomaly-experiments
snavalm/lsr_mood_challenge_2020
Code for the Medical Out of Distribution challenge 2020
MortezaMardani/GAN-Hallucination
This projects investigates the possible hallucinations or adversarial attacks for solving linear inverse problems. The goal is to understand the possible hallucinations, define metrics to quantify the hallucination, and find regularization techniques to make deep reconstruction nets robust against hallucination.
ninatu/mood_challenge
Medical Out-of-Distribution Analysis Challenge MICCAI 2020 Solution
snavalm/ifl_unsup_anom_det
mikek64/image_text_labeling
Labeling text from images with machine learning