Beating the bookies with their own numbers - and how the online sports betting market is rigged
Kaunitz et al.: https://arxiv.org/abs/1710.02824
#Gambling #ComputerScience #Statistics
Kaunitz et al.: https://arxiv.org/abs/1710.02824
#Gambling #ComputerScience #Statistics
arXiv.org
Beating the bookies with their own numbers - and how the online...
The online sports gambling industry employs teams of data analysts to build forecast models that turn the odds at sports games in their favour. While several betting strategies have been proposed...
Stabilizing the Lottery Ticket Hypothesis
Frankle et al.: https://arxiv.org/abs/1903.01611
#ArtificialIntelligence #DeepLearning #NeuralNetworks
Frankle et al.: https://arxiv.org/abs/1903.01611
#ArtificialIntelligence #DeepLearning #NeuralNetworks
Table-Based Neural Units: Fully Quantizing Networks for Multiply-Free Inference
Covell et al.: https://arxiv.org/abs/1906.04798
#ArtificialIntelligence #DeepLearning #MachineLearning
Covell et al.: https://arxiv.org/abs/1906.04798
#ArtificialIntelligence #DeepLearning #MachineLearning
arXiv.org
Table-Based Neural Units: Fully Quantizing Networks for...
In this work, we propose to quantize all parts of standard classification
networks and replace the activation-weight--multiply step with a simple
table-based lookup. This approach results in...
networks and replace the activation-weight--multiply step with a simple
table-based lookup. This approach results in...
Understanding Generalization through Visualizations. arxiv.org/abs/1906.03291
arXiv.org
Understanding Generalization through Visualizations
The power of neural networks lies in their ability to generalize to unseen data, yet the underlying reasons for this phenomenon remain elusive. Numerous rigorous attempts have been made to explain...
Adaptive Nonparametric Variational Autoencoder. arxiv.org/abs/1906.03288
Stanford researchers develop artificial intelligence tool to help detect brain aneurysms
Neural net for brain aneurysms detection
Andrew ng
https://news.stanford.edu/2019/06/07/ai-tool-helps-radiologists-detect-brain-aneurysms/
Neural net for brain aneurysms detection
Andrew ng
https://news.stanford.edu/2019/06/07/ai-tool-helps-radiologists-detect-brain-aneurysms/
Stanford News
AI tool helps radiologists detect brain aneurysms | Stanford News
Radiologists improved their diagnoses of brain aneurysms with the help of AI algorithm.
Write With Transformer
Built by the Hugging Face team: https://transformer.huggingface.co
#ArtificialIntelligence #MachineLearning #GPT2 #GenerativePreTrainedTransformer
Built by the Hugging Face team: https://transformer.huggingface.co
#ArtificialIntelligence #MachineLearning #GPT2 #GenerativePreTrainedTransformer
Deep Flow-Guided Video Inpainting
Xu et al.: https://nbei.github.io/video-inpainting.html
#AritifcialIntelligence #DeepLearning #MachineLearning
Xu et al.: https://nbei.github.io/video-inpainting.html
#AritifcialIntelligence #DeepLearning #MachineLearning
TensorNetwork: A Library for Physics and Machine Learning
“TensorNetwork is an open source library for implementing tensor network algorithms. Tensor networks are sparse data structures originally designed for simulating quantum many-body physics, but are currently also applied in a number of other research areas, including machine learning. Authors demonstrate the use of the API with applications both physics and machine learning, with details appearing in companion papers.”
Paper: https://arxiv.org/pdf/1905.01330.pdf
“TensorNetwork is an open source library for implementing tensor network algorithms. Tensor networks are sparse data structures originally designed for simulating quantum many-body physics, but are currently also applied in a number of other research areas, including machine learning. Authors demonstrate the use of the API with applications both physics and machine learning, with details appearing in companion papers.”
Paper: https://arxiv.org/pdf/1905.01330.pdf
Getting Started With MarathonEnvs v0.5.0a
Blog by Joe Booth: https://towardsdatascience.com/gettingstartedwithmarathonenvs-v0-5-0a-c1054a0b540c
#MachineLearning #ArtificialIntelligence #DeepLearning #ReinforcementLearning #Robotics
Blog by Joe Booth: https://towardsdatascience.com/gettingstartedwithmarathonenvs-v0-5-0a-c1054a0b540c
#MachineLearning #ArtificialIntelligence #DeepLearning #ReinforcementLearning #Robotics
Medium
Getting Started With MarathonEnvs v0.5.0a
I have spent the last two years learning Reinforcement Learning. I created Marathon Environments to help explore the applicability of…
The Neural Aesthetic is finished! Notes and around 30 hours of video lectures
The Neural Aesthetic @ ITP-NYU, Fall 2018
Gene Kogan
https://ml4a.github.io/classes/itp-F18/
The Neural Aesthetic @ ITP-NYU, Fall 2018
Gene Kogan
https://ml4a.github.io/classes/itp-F18/
Is Optimization a Sufficient Language for Understanding Deep Learning?
https://www.offconvex.org/2019/06/03/trajectories/
https://www.offconvex.org/2019/06/03/trajectories/
Off the convex path
Is Optimization a Sufficient Language for Understanding Deep Learning?
Algorithms off the convex path.
iPython notebook for Attentive Neural Processes
https://arxiv.org/pdf/1901.05761.pdf
A special case are Neural Processes
https://arxiv.org/pdf/1807.01622.pdf
Try running the code on your browser (or phone) at:
https://colab.research.google.com/github/deepmind/neural-processes/blob/master/attentive_neural_process.ipynb
https://arxiv.org/pdf/1901.05761.pdf
A special case are Neural Processes
https://arxiv.org/pdf/1807.01622.pdf
Try running the code on your browser (or phone) at:
https://colab.research.google.com/github/deepmind/neural-processes/blob/master/attentive_neural_process.ipynb
lecture notes from course on optimization for machine learning
Elad Hazan
https://drive.google.com/file/d/1GIDnw7T-NT4Do3eC0B5kYJlzwOs6nzIO/view
Elad Hazan
https://drive.google.com/file/d/1GIDnw7T-NT4Do3eC0B5kYJlzwOs6nzIO/view
Google Docs
OPTtutorial.pdf
TensorFuzz: Debugging Neural Networks with Coverage-Guided Fuzzing
Augustus Odena and Ian Goodfellow: https://arxiv.org/abs/1807.10875
Code: https://github.com/brain-research/tensorfuzz
#deeplearning #neuralnetworks #technology #innovation
Augustus Odena and Ian Goodfellow: https://arxiv.org/abs/1807.10875
Code: https://github.com/brain-research/tensorfuzz
#deeplearning #neuralnetworks #technology #innovation
arXiv.org
TensorFuzz: Debugging Neural Networks with Coverage-Guided Fuzzing
Machine learning models are notoriously difficult to interpret and debug. This is particularly true of neural networks. In this work, we introduce automated software testing techniques for neural...
ArtificialIntelligenceArticles
TensorNetwork: A Library for Physics and Machine Learning “TensorNetwork is an open source library for implementing tensor network algorithms. Tensor networks are sparse data structures originally designed for simulating quantum many-body physics, but are…
Google TensorNetwork Library Dramatically Accelerates ML & Physics Tasks
https://medium.com/syncedreview/google-tensornetwork-library-dramatically-accelerates-ml-physics-tasks-8c7011e0f7b0
https://medium.com/syncedreview/google-tensornetwork-library-dramatically-accelerates-ml-physics-tasks-8c7011e0f7b0
Medium
Google TensorNetwork Library Dramatically Accelerates ML & Physics Tasks
Originally designed for simulating quantum physics, tensor networks are now increasingly applied for solving machine learning tasks such…
Here are the COMPLETE Lecture notes on Professor Andrew Ng's
Stanford Machine Learning Lecture: https://www.holehouse.org/mlclass/
Stanford Machine Learning Lecture: https://www.holehouse.org/mlclass/
Deep Learning Tools
PDF Version: https://drive.google.com/file/d/1XhngKISDpQgwGlvU-hjXWZb_qfyIYjqN/view
PDF Version: https://drive.google.com/file/d/1XhngKISDpQgwGlvU-hjXWZb_qfyIYjqN/view