Capsule Networks -- A Probabilistic Perspective
Smith et al.: https://arxiv.org/abs/2004.03553
#ArtificialIntelligence #CapsuleNetworks #MachineLearning
Smith et al.: https://arxiv.org/abs/2004.03553
#ArtificialIntelligence #CapsuleNetworks #MachineLearning
TTNet: Real-time temporal and spatial video analysis of table tennis
Voeikov et al.: https://arxiv.org/abs/2004.09927
#ArtificialIntelligence #DeepLearning #MachineLearning
Voeikov et al.: https://arxiv.org/abs/2004.09927
#ArtificialIntelligence #DeepLearning #MachineLearning
A Metric Learning Reality Check
Musgrave et al.: https://arxiv.org/abs/2003.08505
"Our results show that when hyperparameters are properly tuned via cross-validation, most methods perform similarly to one another"
#ArtificialIntelligence #DeepLearning #MachineLearning
Musgrave et al.: https://arxiv.org/abs/2003.08505
"Our results show that when hyperparameters are properly tuned via cross-validation, most methods perform similarly to one another"
#ArtificialIntelligence #DeepLearning #MachineLearning
MediaPipe Hand
MediaPipe Hand is a high-fidelity hand and finger tracking solution. GitHub : https://github.com/google/mediapipe
#DeepLearning #MachineLearning #MediaPipe
MediaPipe Hand is a high-fidelity hand and finger tracking solution. GitHub : https://github.com/google/mediapipe
#DeepLearning #MachineLearning #MediaPipe
GitHub
GitHub - google-ai-edge/mediapipe: Cross-platform, customizable ML solutions for live and streaming media.
Cross-platform, customizable ML solutions for live and streaming media. - google-ai-edge/mediapipe
Neuroevolution of Self-Interpretable Agents
Tang et al.: https://arxiv.org/abs/2003.08165
#NeuralComputing #EvolutionaryComputing #MachineLearning
Tang et al.: https://arxiv.org/abs/2003.08165
#NeuralComputing #EvolutionaryComputing #MachineLearning
Playing Atari with Six Neurons
Cuccu et al.: https://arxiv.org/abs/1806.01363
#MachineLearning #ArtificialIntelligence #NeuralComputing
Cuccu et al.: https://arxiv.org/abs/1806.01363
#MachineLearning #ArtificialIntelligence #NeuralComputing
arXiv.org
Playing Atari with Six Neurons
Deep reinforcement learning, applied to vision-based problems like Atari games, maps pixels directly to actions; internally, the deep neural network bears the responsibility of both extracting...
List of Open-Source RL Algorithms
By Sergey Kolesnikov, https://docs.google.com/spreadsheets/d/1EeFPd-XIQ3mq_9snTlAZSsFY7Hbnmd7P5bbT8LPuMn0/edit#gid=0
#DeepLearning #MachineLearning #ReinforcementLearning
By Sergey Kolesnikov, https://docs.google.com/spreadsheets/d/1EeFPd-XIQ3mq_9snTlAZSsFY7Hbnmd7P5bbT8LPuMn0/edit#gid=0
#DeepLearning #MachineLearning #ReinforcementLearning
Google Docs
Open-source RL
Full Stack Deep Learning
Tobin et al.: https://course.fullstackdeeplearning.com
#ArtificialIntelligence #DeepLearning #MachineLearning
Tobin et al.: https://course.fullstackdeeplearning.com
#ArtificialIntelligence #DeepLearning #MachineLearning
Fullstackdeeplearning
Full Stack Deep Learning | Full Stack Deep Learning
Full Stack Deep Learning helps you bridge the gap from training machine learning models to deploying AI systems in the real world.
Deriving Differential Target Propagation from Iterating Approximate Inverses
Yoshua Bengio : https://arxiv.org/abs/2007.15139
#ArtificialIntelligence #DeepLearning #MachineLearning
Yoshua Bengio : https://arxiv.org/abs/2007.15139
#ArtificialIntelligence #DeepLearning #MachineLearning
Analyses of Deep Learning (STATS 385)
Stanford University, Fall 2019 : https://stats385.github.io/lecture_videos
#ArtificialIntelligence #DeepLearning #MachineLearning
Stanford University, Fall 2019 : https://stats385.github.io/lecture_videos
#ArtificialIntelligence #DeepLearning #MachineLearning