Bayesian Deep Learning - NeurIPS 2019 Workshop
Friday, December 13, 2019 — Vancouver Convention Center, Vancouver, Canada : http://bayesiandeeplearning.org
#bayesian #deeplearning #neurips2019
Friday, December 13, 2019 — Vancouver Convention Center, Vancouver, Canada : http://bayesiandeeplearning.org
#bayesian #deeplearning #neurips2019
bayesiandeeplearning.org
Bayesian Deep Learning Workshop | NeurIPS 2021
Bayesian Deep Learning Workshop at NeurIPS 2021 — Tuesday, December 14, 2021, Virtual.
We just released our #NeurIPS2019 Multimodal Model-Agnostic Meta-Learning (MMAML) code for learning few-shot image classification, which extends MAML to multimodal task distributions (e.g. learning from multiple datasets). The code contains #PyTorch implementations of our model and two baselines (MAML and Multi-MAML) as well as the scripts to evaluate these models to five popular few-shot learning datasets: Omniglot, Mini-ImageNet, FC100 (CIFAR100), CUB-200-2011, and FGVC-Aircraft.
Code: https://github.com/shaohua0116/MMAML-Classification
Paper: https://arxiv.org/abs/1910.13616
#NeurIPS #MachineLearning #ML #code
Code: https://github.com/shaohua0116/MMAML-Classification
Paper: https://arxiv.org/abs/1910.13616
#NeurIPS #MachineLearning #ML #code
GitHub
GitHub - shaohua0116/MMAML-Classification: An official PyTorch implementation of “Multimodal Model-Agnostic Meta-Learning via Task…
An official PyTorch implementation of “Multimodal Model-Agnostic Meta-Learning via Task-Aware Modulation” (NeurIPS 2019) by Risto Vuorio*, Shao-Hua Sun*, Hexiang Hu, and Joseph J. Lim - GitHub - sh...
Tensor Programs I: Wide Feedforward or Recurrent Neural Networks of Any Architecture are Gaussian Processes
Greg Yang : https://arxiv.org/abs/1910.12478
#ArtificialIntelligence #DeepLearning #NeurIPS2019
Greg Yang : https://arxiv.org/abs/1910.12478
#ArtificialIntelligence #DeepLearning #NeurIPS2019
A Prior of a Googol Gaussians: a Tensor Ring Induced Prior for Generative Models
Kuznetsov et al.: https://arxiv.org/abs/1910.13148
#MachineLearning #NeurIPS #NeurIPS2019
Kuznetsov et al.: https://arxiv.org/abs/1910.13148
#MachineLearning #NeurIPS #NeurIPS2019
arXiv.org
A Prior of a Googol Gaussians: a Tensor Ring Induced Prior for...
Generative models produce realistic objects in many domains, including text, image, video, and audio synthesis. Most popular models---Generative Adversarial Networks (GANs) and Variational...
NeurIPS 2019 Paper Awards
Neural Information Processing Systems Conference : https://medium.com/@NeurIPSConf/neurips-2019-paper-awards-807e41d0c1e
#ArtificialIntelligence #NeurIPS #NeurIPS2019
Neural Information Processing Systems Conference : https://medium.com/@NeurIPSConf/neurips-2019-paper-awards-807e41d0c1e
#ArtificialIntelligence #NeurIPS #NeurIPS2019
Medium
NeurIPS 2019 Paper Awards
With this blog post, it is our pleasure to unveil the NeurIPS paper awards for 2019, and share more information on the selection process…
"Interpretable comparison of distributions and models"
Arthur Gretton, Dougal Sutherland, Wittawat Jitkrittum
Slides :
Part 1: http://gatsby.ucl.ac.uk/~gretton/papers/neurips19_1.pdf
Part 2: http://gatsby.ucl.ac.uk/~gretton/papers/neurips19_2.pdf
Part 3: http://gatsby.ucl.ac.uk/~gretton/papers/neurips19_3.pdf
#ArtificialIntelligence #MachineLearning #NeurIPS2019
Arthur Gretton, Dougal Sutherland, Wittawat Jitkrittum
Slides :
Part 1: http://gatsby.ucl.ac.uk/~gretton/papers/neurips19_1.pdf
Part 2: http://gatsby.ucl.ac.uk/~gretton/papers/neurips19_2.pdf
Part 3: http://gatsby.ucl.ac.uk/~gretton/papers/neurips19_3.pdf
#ArtificialIntelligence #MachineLearning #NeurIPS2019
#NeurIPS2019_2019-12-09_19-49-34.xlsx
View an interactive version of this graph (experimental) https://nodexlgraphgallery.org/Pages/Graph.aspx?graphID=218538
View an interactive version of this graph (experimental) https://nodexlgraphgallery.org/Pages/Graph.aspx?graphID=218538
Neural Ordinary Differential Equations for Semantic Segmentation of Individual Colon Glands
Hans Pinckaers, Geert Litjens : https://arxiv.org/abs/1910.10470
GitHub : https://github.com/DIAGNijmegen/neural-odes-segmentation
#MedNeurIPS #NeurIPS #NeurIPS2019
Hans Pinckaers, Geert Litjens : https://arxiv.org/abs/1910.10470
GitHub : https://github.com/DIAGNijmegen/neural-odes-segmentation
#MedNeurIPS #NeurIPS #NeurIPS2019
arXiv.org
Neural Ordinary Differential Equations for Semantic Segmentation...
Automated medical image segmentation plays a key role in quantitative research and diagnostics. Convolutional neural networks based on the U-Net architecture are the state-of-the-art. A key...
"Differentiable Convex Optimization Layers"
CVXPY creates powerful new PyTorch and TensorFlow layers
Agrawal et al.: https://locuslab.github.io/2019-10-28-cvxpylayers/
#PyTorch #TensorFlow #NeurIPS2019
CVXPY creates powerful new PyTorch and TensorFlow layers
Agrawal et al.: https://locuslab.github.io/2019-10-28-cvxpylayers/
#PyTorch #TensorFlow #NeurIPS2019
locuslab.github.io
Differentiable Convex Optimization Layers
CVXPY creates powerful new PyTorch and TensorFlow layers
NeurIPS 2019 Paper Awards
Neural Information Processing Systems Conference : https://medium.com/@NeurIPSConf/neurips-2019-paper-awards-807e41d0c1e
@ArtificialIntelligenceArticles
#ArtificialIntelligence #NeurIPS #NeurIPS2019
https://t.me/ArtificialIntelligenceArticles
Neural Information Processing Systems Conference : https://medium.com/@NeurIPSConf/neurips-2019-paper-awards-807e41d0c1e
@ArtificialIntelligenceArticles
#ArtificialIntelligence #NeurIPS #NeurIPS2019
https://t.me/ArtificialIntelligenceArticles
Medium
NeurIPS 2019 Paper Awards
With this blog post, it is our pleasure to unveil the NeurIPS paper awards for 2019, and share more information on the selection process…
Machine Learning on Graphs #NeurIPS2019
Michael Galkin : https://medium.com/@mgalkin/machine-learning-on-graphs-neurips-2019-875eecd41069
#GraphNeuralNetworks #NLP
Michael Galkin : https://medium.com/@mgalkin/machine-learning-on-graphs-neurips-2019-875eecd41069
#GraphNeuralNetworks #NLP
Medium
Machine Learning on Graphs @ NeurIPS 2019
If you still had any doubts — it’s time to admit. Machine Learning on Graphs becomes a first-class citizen at AI conferences while being…
NeurIPS 2019 Notes
David Abel : https://david-abel.github.io/notes/neurips_2019.pdf
#ArtificialIntelligence #DeepLearning #NeurIPS2019
David Abel : https://david-abel.github.io/notes/neurips_2019.pdf
#ArtificialIntelligence #DeepLearning #NeurIPS2019
From deep learning to mechanistic understanding in neuroscience: the structure of retinal prediction
https://papers.nips.cc/paper/9060-from-deep-learning-to-mechanistic-understanding-in-neuroscience-the-structure-of-retinal-prediction
#DeepLearning #Neuroscience #NeurIPS2019
https://papers.nips.cc/paper/9060-from-deep-learning-to-mechanistic-understanding-in-neuroscience-the-structure-of-retinal-prediction
#DeepLearning #Neuroscience #NeurIPS2019
papers.nips.cc
From deep learning to mechanistic understanding in neuroscience: the structure of retinal prediction
Electronic Proceedings of Neural Information Processing Systems
Look at Tackling Climate Change with ML 2 on SlidesLive! #NeurIPS2019 climate change workshop, including a panel with our very own Andrew Ng, Yoshua Bengio, Jeff Dean, Carla Gomes, and Lester Mackey
https://slideslive.com/38922107/tackling-climate-change-with-ml-2
https://slideslive.com/38922107/tackling-climate-change-with-ml-2
SlidesLive
Leveraging digitalization for urban solutions in the Anthropocene
"Differentiable Convex Optimization Layers"
CVXPY creates powerful new PyTorch and TensorFlow layers
Agrawal et al.: https://locuslab.github.io/2019-10-28-cvxpylayers/
#PyTorch #TensorFlow #NeurIPS2019
CVXPY creates powerful new PyTorch and TensorFlow layers
Agrawal et al.: https://locuslab.github.io/2019-10-28-cvxpylayers/
#PyTorch #TensorFlow #NeurIPS2019
locuslab.github.io
Differentiable Convex Optimization Layers
CVXPY creates powerful new PyTorch and TensorFlow layers
From deep learning to mechanistic understanding in neuroscience: the structure of retinal prediction
Tanaka et al.: https://papers.nips.cc/paper/9060-from-deep-learning-to-mechanistic-understanding-in-neuroscience-the-structure-of-retinal-prediction
#DeepLearning #Neuroscience #NeurIPS2019
Tanaka et al.: https://papers.nips.cc/paper/9060-from-deep-learning-to-mechanistic-understanding-in-neuroscience-the-structure-of-retinal-prediction
#DeepLearning #Neuroscience #NeurIPS2019
papers.nips.cc
From deep learning to mechanistic understanding in neuroscience: the structure of retinal prediction
Electronic Proceedings of Neural Information Processing Systems
Neural Ordinary Differential Equations for Semantic Segmentation of Individual Colon Glands
Hans Pinckaers, Geert Litjens : https://arxiv.org/abs/1910.10470
GitHub : https://github.com/DIAGNijmegen/neural-odes-segmentation
#MedNeurIPS #NeurIPS #NeurIPS2019
Hans Pinckaers, Geert Litjens : https://arxiv.org/abs/1910.10470
GitHub : https://github.com/DIAGNijmegen/neural-odes-segmentation
#MedNeurIPS #NeurIPS #NeurIPS2019
arXiv.org
Neural Ordinary Differential Equations for Semantic Segmentation...
Automated medical image segmentation plays a key role in quantitative research and diagnostics. Convolutional neural networks based on the U-Net architecture are the state-of-the-art. A key...
Efficient Graph Generation with Graph Recurrent Attention Networks
Liao et al.: https://arxiv.org/abs/1910.00760
Code: https://github.com/lrjconan/GRAN
#Graph #NeuralNetworks #NeurIPS #NeurIPS2019
Liao et al.: https://arxiv.org/abs/1910.00760
Code: https://github.com/lrjconan/GRAN
#Graph #NeuralNetworks #NeurIPS #NeurIPS2019
GitHub
GitHub - lrjconan/GRAN: Efficient Graph Generation with Graph Recurrent Attention Networks, Deep Generative Model of Graphs, Graph…
Efficient Graph Generation with Graph Recurrent Attention Networks, Deep Generative Model of Graphs, Graph Neural Networks, NeurIPS 2019 - lrjconan/GRAN