DeepLearning
A collection of research papers, datasets and software on Deep Learning
https://github.com/axruff/DeepLearning
Last synced: 12 days ago
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Reinforcement Learning
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Inverse Reinforcement Learning
- 2018 - An Unsupervised Learning Model for Deformable Medical Image Registration
- 2018 - VoxelMorph: A Learning Framework for Deformable Medical Image Registration
- 2019 - A Deep Learning Framework for Unsupervised Affine and Deformable Image Registration
- 2019 - Unsupervised Learning of Probabilistic Diffeomorphic Registration for Images and Surfaces
- 2020 - RANSAC-Flow: generic two-stage image alignment
- Video-to-Video Synthesis (2018)
- 2017 - PWC-Net: CNNs for Optical Flow Using Pyramid, Warping, and Cost Volume - pwc)
- 2020 - Softmax Splatting for Video Frame Interpolation - splatting)
- 2017 - **[TOFlow
- 2020 - Automating turbulence modelling by multi-agent reinforcement learning
- 2017 - "Zero-Shot" Super-Resolution using Deep Internal Learning
- 2018 - Residual Dense Network for Image Restoration
- 2018 - Image Super-Resolution Using Very Deep Residual Channel Attention Networks
- 2019 - Noise2Self: Blind Denoising by Self-Supervision
- 2020 - Improving Blind Spot Denoising for Microscopy
- 2021 - Denoising-based Image Compression for Connectomics
- 2018 - Image Inpainting for Irregular Holes Using Partial Convolutions - Keras)
- 2017 - Globally and Locally Consistent Image Completion
- 2017 - Generative Image Inpainting with Contextual Attention
- 2018 - Free-Form Image Inpainting with Gated Convolution
- Photo-realistic single image super-resolution using a generative adversarial network (2016)
- A Closed-form Solution to Photorealistic Image Stylization (2018)
- 2021 - COIN: COmpression with Implicit Neural representations
- **[pix2code
- Fast Interactive Object Annotation with Curve-GCN (2019)
- 2017 - Learning Fashion Compatibility with Bidirectional LSTMs
- 2020 - A Systematic Literature Review on the Use of Deep Learning in Software Engineering Research
- 2020 - Fourier Neural Operator for Parametric Partial Differential Equations
- **Caffe**: Convolutional Architecture for Fast Feature Embedding
- **PySyft**: A generic framework for privacy preserving deep learning
- **Crypten**: A framework for Privacy Preserving Machine Learning
- **[Snorkel
- **[mlflow
- OpenAI Microscope
- **[Rapid
- **[DALI
- **[PhotonAI
- **[DeepImageJ
- **[ImJoy
- **[BioImage.IO
- **[DeepImageTranslator
- **[OpenMMLab
- 2016 - An Analysis of Deep Neural Network Models for Practical Applications
- 2017 - Revisiting Unreasonable Effectiveness of Data in Deep Learning Era
- 2019 - High-performance medicine: the convergence of human and artificial intelligence
- 2020 - Maithra Raghu, Eric Schmidt. A Survey of Deep Learning for Scientific Discovery
- 2021 - Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans
- 2016 - Building Machines That Learn and Think Like People
- 2016 - A Berkeley View of Systems Challenges for AI
- 2018 - Deep Learning: A Critical Appraisal
- 2018 - When Will AI Exceed Human Performance? Evidence from AI Experts
- 2018 - The Malicious Use of Artificial Intelligence: Forecasting, Prevention, and Mitigation
- 2018 - Deciphering China’s AI Dream: The context, components, capabilities, and consequences of China’s strategy to lead the world in AI
- 2018 - The Surprising Creativity of Digital Evolution: A Collection of Anecdotes from the Evolutionary Computation and Artificial Life Research Communities
- 2019 - Deep Nets: What have they ever done for Vision?
- 2020 - State of AI Report 2020
- 2020 - The role of artificial intelligence in achieving the Sustainable Development Goals
- 2020 - The Next Decade in AI: Four Steps Towards Robust Artificial Intelligence
- 2021 - Why AI is Harder Than We Think by Melanie Mitchell
- 2020 - Reconstructing lost BOLD signal in individual participants using deep machine learning
- 2019 - Deep learning optoacoustic tomography with sparse data
- 2020 - **[Review
- 2020 - Patient-specific reconstruction of volumetric computed tomography images from a single projection view via deep learning.
- 2020 - Automating turbulence modelling by multi-agent reinforcement learning
- 2021 - Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans
- 2020 - The role of artificial intelligence in achieving the Sustainable Development Goals
- MLPerf: A broad ML benchmark suite for measuring performance of ML software frameworks, ML hardware accelerators, and ML cloud platforms.
- 2020 - Reconstructing lost BOLD signal in individual participants using deep machine learning
- 2019 - Deep learning optoacoustic tomography with sparse data
- 2020 - **[Review
- 2020 - Patient-specific reconstruction of volumetric computed tomography images from a single projection view via deep learning.
- 2020 - Automating turbulence modelling by multi-agent reinforcement learning
- 2021 - Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans
- 2020 - The role of artificial intelligence in achieving the Sustainable Development Goals
- 2020 - Reconstructing lost BOLD signal in individual participants using deep machine learning
- 2019 - Deep learning optoacoustic tomography with sparse data
- 2020 - **[Review
- 2020 - Patient-specific reconstruction of volumetric computed tomography images from a single projection view via deep learning.
- 2020 - Automating turbulence modelling by multi-agent reinforcement learning
- 2021 - Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans
- 2020 - The role of artificial intelligence in achieving the Sustainable Development Goals
- 2020 - Reconstructing lost BOLD signal in individual participants using deep machine learning
- 2019 - Deep learning optoacoustic tomography with sparse data
- 2020 - **[Review
- 2020 - Patient-specific reconstruction of volumetric computed tomography images from a single projection view via deep learning.
- 2020 - Automating turbulence modelling by multi-agent reinforcement learning
- 2021 - Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans
- 2020 - The role of artificial intelligence in achieving the Sustainable Development Goals
- 2020 - Reconstructing lost BOLD signal in individual participants using deep machine learning
- 2019 - Deep learning optoacoustic tomography with sparse data
- 2020 - **[Review
- 2020 - Patient-specific reconstruction of volumetric computed tomography images from a single projection view via deep learning.
- 2020 - Automating turbulence modelling by multi-agent reinforcement learning
- 2021 - Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans
- 2020 - The role of artificial intelligence in achieving the Sustainable Development Goals
- 2020 - Reconstructing lost BOLD signal in individual participants using deep machine learning
- 2019 - Deep learning optoacoustic tomography with sparse data
- 2020 - **[Review
- 2020 - Patient-specific reconstruction of volumetric computed tomography images from a single projection view via deep learning.
- 2020 - Automating turbulence modelling by multi-agent reinforcement learning
- 2021 - Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans
- 2020 - The role of artificial intelligence in achieving the Sustainable Development Goals
- 2020 - Reconstructing lost BOLD signal in individual participants using deep machine learning
- 2019 - Deep learning optoacoustic tomography with sparse data
- 2020 - **[Review
- 2020 - Patient-specific reconstruction of volumetric computed tomography images from a single projection view via deep learning.
- 2020 - Automating turbulence modelling by multi-agent reinforcement learning
- 2021 - Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans
- 2020 - The role of artificial intelligence in achieving the Sustainable Development Goals
- 2020 - Reconstructing lost BOLD signal in individual participants using deep machine learning
- 2019 - Deep learning optoacoustic tomography with sparse data
- 2020 - **[Review
- 2020 - Patient-specific reconstruction of volumetric computed tomography images from a single projection view via deep learning.
- 2020 - Automating turbulence modelling by multi-agent reinforcement learning
- 2021 - Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans
- 2020 - The role of artificial intelligence in achieving the Sustainable Development Goals
- 2020 - Reconstructing lost BOLD signal in individual participants using deep machine learning
- 2019 - Deep learning optoacoustic tomography with sparse data
- 2020 - **[Review
- 2020 - Patient-specific reconstruction of volumetric computed tomography images from a single projection view via deep learning.
- 2020 - Automating turbulence modelling by multi-agent reinforcement learning
- 2021 - Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans
- 2020 - The role of artificial intelligence in achieving the Sustainable Development Goals
- 2020 - Reconstructing lost BOLD signal in individual participants using deep machine learning
- 2019 - Deep learning optoacoustic tomography with sparse data
- 2020 - **[Review
- 2020 - Patient-specific reconstruction of volumetric computed tomography images from a single projection view via deep learning.
- 2020 - Automating turbulence modelling by multi-agent reinforcement learning
- 2021 - Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans
- 2020 - The role of artificial intelligence in achieving the Sustainable Development Goals
- 2020 - Reconstructing lost BOLD signal in individual participants using deep machine learning
- 2019 - Deep learning optoacoustic tomography with sparse data
- 2020 - **[Review
- 2020 - Patient-specific reconstruction of volumetric computed tomography images from a single projection view via deep learning.
- 2020 - Automating turbulence modelling by multi-agent reinforcement learning
- 2021 - Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans
- 2020 - The role of artificial intelligence in achieving the Sustainable Development Goals
- 2020 - Reconstructing lost BOLD signal in individual participants using deep machine learning
- 2019 - Deep learning optoacoustic tomography with sparse data
- 2020 - **[Review
- 2020 - Patient-specific reconstruction of volumetric computed tomography images from a single projection view via deep learning.
- 2020 - Automating turbulence modelling by multi-agent reinforcement learning
- 2021 - Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans
- 2020 - The role of artificial intelligence in achieving the Sustainable Development Goals
- 2020 - Reconstructing lost BOLD signal in individual participants using deep machine learning
- 2019 - Deep learning optoacoustic tomography with sparse data
- 2020 - **[Review
- 2020 - Patient-specific reconstruction of volumetric computed tomography images from a single projection view via deep learning.
- 2020 - Automating turbulence modelling by multi-agent reinforcement learning
- 2021 - Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans
- 2020 - The role of artificial intelligence in achieving the Sustainable Development Goals
- **[OPENSURFACES
- 2021 - Medical Segmentation Decathlon. Generalisable 3D Semantic Segmentation
- 2020 - Reconstructing lost BOLD signal in individual participants using deep machine learning
- 2019 - Deep learning optoacoustic tomography with sparse data
- 2020 - **[Review
- 2020 - Patient-specific reconstruction of volumetric computed tomography images from a single projection view via deep learning.
- 2020 - Automating turbulence modelling by multi-agent reinforcement learning
- 2018 - Image Inpainting for Irregular Holes Using Partial Convolutions - Keras)
- 2017 - Globally and Locally Consistent Image Completion
- **Glow**: Compiler for Neural Network hardware accelerators
- **Lucid**: A collection of infrastructure and tools for research in neural network interpretability
- **[Interactive Tools
- **[Efemarai
- **[TorchIO
- **[Ignite
- **[Cadene
- **[PyTorch Toolbelt
- **[PyTorch Lightning
- 2019 - High-performance medicine: the convergence of human and artificial intelligence
- **[ml-surveys [github
- 2021 - Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans
- 2018 - Human-level intelligence or animal-like abilities?
- 2020 - The role of artificial intelligence in achieving the Sustainable Development Goals
- 2019 - High-performance medicine: the convergence of human and artificial intelligence
- 2020 - Reconstructing lost BOLD signal in individual participants using deep machine learning
- 2019 - Deep learning optoacoustic tomography with sparse data
- 2020 - **[Review
- 2020 - Patient-specific reconstruction of volumetric computed tomography images from a single projection view via deep learning.
- 2020 - Automating turbulence modelling by multi-agent reinforcement learning
- 2019 - High-performance medicine: the convergence of human and artificial intelligence
- 2021 - Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans
- 2020 - The role of artificial intelligence in achieving the Sustainable Development Goals
- 2019 - High-performance medicine: the convergence of human and artificial intelligence
- 2020 - Reconstructing lost BOLD signal in individual participants using deep machine learning
- 2019 - Deep learning optoacoustic tomography with sparse data
- 2020 - **[Review
- 2020 - Patient-specific reconstruction of volumetric computed tomography images from a single projection view via deep learning.
- 2020 - Automating turbulence modelling by multi-agent reinforcement learning
- 2021 - BTrack: Bayesian Tracker
- 2019 - High-performance medicine: the convergence of human and artificial intelligence
- 2021 - Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans
- 2020 - The role of artificial intelligence in achieving the Sustainable Development Goals
- 2019 - High-performance medicine: the convergence of human and artificial intelligence
- 2020 - Reconstructing lost BOLD signal in individual participants using deep machine learning
- 2019 - Deep learning optoacoustic tomography with sparse data
- 2020 - **[Review
- 2020 - Patient-specific reconstruction of volumetric computed tomography images from a single projection view via deep learning.
- 2020 - Automating turbulence modelling by multi-agent reinforcement learning
- 2019 - High-performance medicine: the convergence of human and artificial intelligence
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Programming Languages
Categories
Reinforcement Learning
313
Models
95
Optimization and Regularisation
21
Unsupervised Learning
16
Analysis and Interpretability
15
Semi Supervised
15
Pruning and Compression
10
Segmentation
6
Weakly Supervised
6
Optical Flow
4
Multitask Learning
3
Semantic Correspondence
3
Mutual Learning
2
Anomaly Detection
2
Instance Segmentation
2
Interactive Segmentation
1
Transfer Learning
1
Sub Categories
Keywords
machine-learning
7
deep-learning
6
pytorch
5
python
3
tensorflow
2
neural-network
2
ai
2
interactive-tools
1
visualizer
1
tensorflow-lite
1
safetensors
1
onnx
1
numpy
1
ml
1
machinelearning
1
keras
1
deeplearning
1
coreml
1
survey
1
reinforcement-learning
1
recommender-system
1
nlp
1
embeddings
1
computer-vision
1
visualization
1
jupyter-notebook
1
interpretability
1
colab
1
transfer-learning
1
synthetic-data
1
style-transfer
1
generative-model
1
domain-adaptation
1
data-science
1
artificial-intelligence
1
resnext
1
resnet
1
pretrained
1
inception
1
imagenet
1
tta
1
test-time-augmentation
1
segmentation
1
pipeline
1
object-detection
1
kaggle
1
jaccard-loss
1
image-segmentation
1
image-processing
1
image-classification
1