How quantum computing will revolutionise AI and machine learning
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Learning Deformable Object Manipulation from Expert Demonstrations
Manipulating deformable objects is a difficult dilemma in robotics. A recent paper on arXiv.org proposes the Discovering from Demonstration approach...
Self-Supervised Learning of Music-Dance Representation through Explicit-Implicit Rhythm Synchronization
Dancing films are ubiquitous on on the web movie-sharing sites. Therefore, there is a expanding demand for automatically processing dancing...
Duolingo review: Free, fun, easy language learning practice
Pros Desktop and mobile apps are user-friendly Range of questions for 19 distinct languages Variety of platforms Bite-sized lessons Cons...
SYNERgy between SYNaptic consolidation and Experience Replay for general continual learning
Deep neural networks (DNNs) must be capable to constantly get, retain and consolidate awareness. Having said that, they show catastrophic...
FishGym: A High-Performance Physics-based Simulation Framework for Underwater Robot Learning
Bio-encouraged underwater robots have a good deal of advantages, such as robust maneuverability and propulsion performance. However, training their behaviors...
Rethinking Reinforcement Learning based Logic Synthesis
Logic synthesis is an approach for finding equivalent representations of large-scale integrated circuits solved by reinforcement learning (RL) algorithms. Image...
Thalamus: a brain-inspired algorithm for biologically-plausible continual learning and disentangled representations
Animal brains can use environmental changes at many time scales. They leverage the temporal structure to master causal and perfectly-factorized...
Learning Keypoints from Synthetic Data for Robotic Cloth Folding
Robotic manipulation of deformable objects is a difficult activity. However, responsibilities like cloth manipulation are handy in daily options. A...
How can we be sure machine learning is accurate?
Scientists rely significantly on designs trained with equipment studying to present answers to complicated problems. But how do we know...
Perovskite materials would be superior to silicon in PV cells, but manufacturing such cells at scale is a huge hurdle. Machine learning can help. — ScienceDaily
Perovskites are a family of materials that are presently the primary contender to probably replace today's silicon-dependent solar photovoltaics. They...
Orchestrating data for machine learning pipelines
Machine learning (ML) workloads require efficient infrastructure to yield rapid results. Model training relies heavily on large data sets. Funneling...
