The Living Thing / Notebooks - machine learning

The Living Thing / Notebooks :

pytorch — [ #torched ] —
2018-05-04… 2019-11-28
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Audio source separation —
2019-11-04… 2019-11-26
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Probabilistic neural nets — [ This is Machinelearnese for “Bayesian” ] —
2017-01-11… 2019-11-23
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Controllerism — [ Also gestural interfaces, and other fancy words for making thing happen by waving your arms about on stage ] —
2014-11-17… 2019-11-22
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Tunings —
2015-10-29… 2019-11-18
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Auditory features — [ descriptors, maps, representations for audio ] —
2019-11-13… 2019-11-13
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Machine listening — [ Statistical models for audio ] —
2014-10-10… 2019-11-12
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Javascript machine learning —
2017-01-13… 2019-11-09
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ISMIR 2019 — [ Music Nerds in Delft ] —
2019-11-04… 2019-11-09
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Analysis/resynthesis of audio —
2016-01-15… 2019-11-04
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Here’s how I would do art with machine learning if I had to —
2016-06-06… 2019-11-04
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Survey modelling — [ Adjusting for the Lizardman constant ] —
2019-08-29… 2019-10-30
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Inference on graphical models — [ Given what I know about what I know, what do I know? ] —
2017-09-20… 2019-10-28
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Learning in adaptive systems — [ On staring into scopophilic abysses ] —
2019-10-19… 2019-10-19
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Deep learning as a dynamical system —
2018-08-13… 2019-10-15
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Bio computing —
2016-05-29… 2019-10-14
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Why does deep learning work? — [ despite the fact we are totally just making this shit up ] —
2017-05-30… 2019-10-09
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Probabilistic graphical models over continuous index sets —
2014-08-05… 2019-09-25
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Differentiable learning of automata —
2016-10-14… 2019-09-11
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Hierarchical models — [ DAGs, multilevel models, random coefficient models, mixed effect models… ] —
2015-06-07… 2019-08-19
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Causal inference — [ Confounding! This scientist performed miracle graph surgery during an intervention and you won’t believe what happened next ] —
2016-10-26… 2019-08-07
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Neural nets — [ designing the fanciest usable differentiable loss surface ] —
2016-10-14… 2019-05-27
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Natural language processing — [ Dave, although you took very thorough precautions in the pod against my hearing you, I could see your lips move. ] —
2018-01-11… 2019-04-22
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Model interpretation, fairness and trust —
2018-11-29… 2019-02-15
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Overparameterization — [ a.k.a. improper learning ] —
2018-04-04… 2018-12-11
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Machine vision —
2015-01-03… 2018-11-14
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Gesture recognition —
2014-10-17… 2018-11-12
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Compressing artificial neural networks —
2016-10-12… 2018-10-23
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Learnable indexes and hashes —
2018-01-12… 2018-01-12
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Moral calculus —
2014-08-04… 2017-11-21
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Convolutional neural networks —
2017-11-10… 2017-11-10
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Recurrent neural networks —
2016-06-16… 2017-10-25
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Model interpretation —
2016-09-01… 2017-10-13
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Distributed sensing and swarm sensing —
2014-10-13… 2017-10-12
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Learning graphical models from data — [ what is independent of what ] —
2017-09-20… 2017-09-27
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(Probabilistic) graphical models —
2014-08-05… 2017-09-11
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Brains — [ Neural networks made of real neurons, in functioning brains ] —
2014-11-03… 2017-08-15
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Quantum-probabilistic graphical models —
2017-08-07… 2017-08-07
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Generalisation in neural networks — [ Generalisation for street fighters ] —
2017-02-12… 2017-06-20
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Marketing psychology —
2017-04-27… 2017-05-29
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Machine learning for physics — [ Turbulent mixing at the boundary between two disciplines with differing inertia ] —
2017-05-15… 2017-05-25
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Human behaviour control, methods for —
2017-04-04… 2017-04-04
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Entity embeddings —
2017-04-01… 2017-04-01
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Musical metrics and manifolds —
2014-09-26… 2017-03-27
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Random neural networks —
2017-02-17… 2017-02-19
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Neural network activation functions —
2017-01-12… 2017-01-12
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Greatest hits —
2016-11-19… 2016-12-12
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UNSW Stats reading group 2016 - Causal DAGs — [ An introduction to conditional independence DAGs and their use for causal data. ] —
2016-10-17… 2016-10-21
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Inference from disorder —
2016-10-19… 2016-10-19
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Generalised linear models —
2016-03-24… 2016-08-31
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Probably Approximately Correct —
2014-11-24… 2016-05-29
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Pattern machine —
2011-06-27… 2015-11-24
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Grammatical inference —
2011-05-30… 2015-02-19
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