🛠 ZeroGen: Efficient Zero-shot Learning via Dataset Generation
Github: https://github.com/jiacheng-ye/zerogen
Paper: https://arxiv.org/abs/2202.07922v1
Dataset: https://paperswithcode.com/dataset/sst
@Machine_learn
Github: https://github.com/jiacheng-ye/zerogen
Paper: https://arxiv.org/abs/2202.07922v1
Dataset: https://paperswithcode.com/dataset/sst
@Machine_learn
This media is not supported in your browser
VIEW IN TELEGRAM
🐭 pymdp: A Python library for active inference in discrete state spaces
Github: https://github.com/infer-actively/pymdp
Paper: https://arxiv.org/abs/2201.03904v1
Docs: https://pymdp-rtd.readthedocs.io/
Tasks: https://paperswithcode.com/task/bayesian-inference
@Machine_learn
Github: https://github.com/infer-actively/pymdp
Paper: https://arxiv.org/abs/2201.03904v1
Docs: https://pymdp-rtd.readthedocs.io/
Tasks: https://paperswithcode.com/task/bayesian-inference
@Machine_learn
✨ Uniformer: Unified Transformer for Efficient Spatiotemporal Representation Learning
Github: https://github.com/sense-x/uniformer
Paper: https://arxiv.org/abs/2201.04676v1
Tasks: https://paperswithcode.com/dataset/kinetics-600
@Machine_learn
Github: https://github.com/sense-x/uniformer
Paper: https://arxiv.org/abs/2201.04676v1
Tasks: https://paperswithcode.com/dataset/kinetics-600
@Machine_learn
Coverage-Guided Tensor Compiler Fuzzing with Joint IR-Pass Mutation
Github: https://github.com/tzer-anonbot/tzer
Docs: https://tzer.readthedocs.io/en/latest/markdown/artifact.html
Paper: https://arxiv.org/abs/2202.09947v1
@Machine_learn
Github: https://github.com/tzer-anonbot/tzer
Docs: https://tzer.readthedocs.io/en/latest/markdown/artifact.html
Paper: https://arxiv.org/abs/2202.09947v1
@Machine_learn
GitHub
GitHub - Tzer-AnonBot/tzer: Tzer: TVM Implementation of "Coverage-Guided Tensor Compiler Fuzzing with Joint IR-Pass Mutation (OOPSLA'22)“.
Tzer: TVM Implementation of "Coverage-Guided Tensor Compiler Fuzzing with Joint IR-Pass Mutation (OOPSLA'22)“. - Tzer-AnonBot/tzer
20191119_Ahmadi_2.pdf
26.4 MB
EEG microstate and functional brain network features for
classification of epilepsy and PNES #EEG #Thesis @Machine_learn
classification of epilepsy and PNES #EEG #Thesis @Machine_learn
electronics-10-03037.pdf
2.5 MB
A Survey on EEG Signal Processing Techniques and Machine
Learning: Applications to the Neurofeedback of
Autobiographical Memory Deficits in Schizophrenia #EEG #ML #DL @Machine_learn
Learning: Applications to the Neurofeedback of
Autobiographical Memory Deficits in Schizophrenia #EEG #ML #DL @Machine_learn
DeepFusionMOT: A 3D Multi-Object Tracking Framework Based on Camera-LiDAR Fusion with Deep Association
Github: https://github.com/wangxiyang2022/DeepFusionMOT
Paper: https://arxiv.org/abs/2202.12100v1
Dataset: https://paperswithcode.com/dataset/kitti
@Machine_learn
Github: https://github.com/wangxiyang2022/DeepFusionMOT
Paper: https://arxiv.org/abs/2202.12100v1
Dataset: https://paperswithcode.com/dataset/kitti
@Machine_learn
Overcoming catastrophic forgetting in neural networks
Github: https://github.com/ContinualAI/avalanche
Paper: https://arxiv.org/abs/1612.00796v2
Dataset: https://paperswithcode.com/dataset/asc-til-19-tasks
@Machine_learn
Github: https://github.com/ContinualAI/avalanche
Paper: https://arxiv.org/abs/1612.00796v2
Dataset: https://paperswithcode.com/dataset/asc-til-19-tasks
@Machine_learn
Machine Learning for Mechanical Ventilation Control
http://ai.googleblog.com/2022/02/machine-learning-for-mechanical.html
@Machine_learn
http://ai.googleblog.com/2022/02/machine-learning-for-mechanical.html
@Machine_learn
research.google
Machine Learning for Mechanical Ventilation Control
Posted by Daniel Suo, Software Engineer and Elad Hazan, Research Scientist, Google Research, on behalf of the Google AI Princeton Team Mechanical...