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What do GFlowNets and Variational Inference Have in Common?

What do GFlowNets and Variational Inference Have in Common?
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"Bayesian Gabor Network with Uncertainty Estimation for Pedestrian Lane" by Hoang Thanh Le, Son Lam Phung et al.

Automatic pedestrian lane detection is a challenging problem that is of great interest in assistive navigation and autonomous driving. Such a detection system must cope well with variations in lane surfaces and illumination conditions so that a vision-impaired user can navigate safely in unknown environments. This paper proposes a new lightweight Bayesian Gabor Network (BGN) for camera-based detection of pedestrian lanes in unstructured scenes. In our approach, each Gabor parameter is represented as a learnable Gaussian distribution using variational Bayesian inference. For the safety of vision-impaired users, in addition to an output segmentation map, the network provides two full-resolution maps of aleatoric uncertainty and epistemic uncertainty as well-calibrated confidence measures. Our Gabor-based method has fewer weights than the standard CNNs, therefore it is less prone to overfitting and requires fewer operations to compute. Compared to the state-of-the-art semantic segmentatio ....

Bayesian Gabor Network , Assistive And Autonomous Navigation , Bayes Methods , Bayesian Gabor Network , Image Segmentation , Lane Detection , Edestrian Lane Detection , Uncertainty Estimation , Variational Inference ,

New research shows that near-term quantum computers can learn to reason

Apr 1, 2021 03:18 EDT
with 3 comments
The applications and development of quantum computers have steadily picked up pace in the last few years. We ve seen researchers applying this novel method of computation in a variety of domains including quantum chemistry, fluid dynamics research, open problems, and even machine learning, all with promising results.
Continuing this trend, UK-based startup Cambridge Quantum Computing (CQC) has now demonstrated that quantum computers can learn to reason . Confusing at first, this claim is based upon new research coming out of CQC. Dr. Mattia Fiorentini, Head of Quantum Machine Learning at the firm, and his team of researchers investigated using quantum computers for Variational Inference. ....

United Kingdom , Mattia Fiorentini , Kernelized Stein , Bayesian Networks , United Kingdom Based , Cambridge Quantum Computing , Quantum Machine Learning , Variational Inference , Hidden Markov Model , ஒன்றுபட்டது கிஂக்டம் , ஒன்றுபட்டது கிஂக்டம் அடிப்படையிலானது , கேம்பிரிட்ஜ் குவாண்டம் கணினி , குவாண்டம் இயந்திரம் கற்றல் , மறைக்கப்பட்டுள்ளது மார்க்கோவ் மாதிரி ,