I'm not sure how I've missed them until now, but the “#Probabilistic #Machine #Learning” book series by Kevin P. Murphy is outstanding. Such a comprehensive yet accessible distillation of concepts making it an excellent (teaching) reference. Just take a look at the contents page of Book 2: Advanced Topics! https://probml.github.io/pml-book/ and did I mention its accompanying #python #Github repo? https://github.com/probml/pyprobml #statistics
#probabilistic #machine #learning #python #GitHub #statistics
TODO: Try in future
"Pyro is a #probabilistic #programming language built on #Python and PyTorch."
#probabilistic #programming #python
“A team of researchers from the Massachusetts Institute of Technology has achieved a milestone in #quantum technologies, demonstrating for the first time the control of quantum randomness.”
"Our discovery of controllable quantum randomness not only allows us to revisit decades-old concepts in quantum #optics but also opens up potential in #probabilistic computing and ultra-precise field sensing."
“Probabilistic computing [is] well-suited to simulate physical phenomena and tackle optimization problems where multiple solutions could exist and where exploration of various possibilities can lead to a better solution.”
https://phys.org/news/2023-07-quantum-fluctuations-potential-ultra-precise-field.html
#quantum #optics #probabilistic #mit #physics
Finally, I managed to write another blog post. In the post I am essentially talking about works (mostly) by Alessandro Rudi and coauthors on #tractable #probabilistic models such as #mixtures with #negative parameters.
Check out: https://trappmartin.github.io/website/post/2023_06_snf/
I will likely go into details of some of the aspects of this new family of models in follow up posts.
Let me know what you think about the blog post. Too high level or just right? Or any other feedback?
#tractable #probabilistic #mixtures #negative
I'm back in Helsinki and super excited about my course on #tractable #probabilistic modelling at #aaltouniversity! Looking forward to explore the space and limitations of #tractable computations in #probabilisticmodels with students.
#tractable #probabilistic #aaltouniversity #probabilisticmodels
Preliminary list of FedCSIS Keynotes has been announced. Come to the conference to listen to Prof. Marta Kwiatkowska, Professor of Computing Systems and Fellow of Trinity College, University of Oxford. Abstract available at: https://lnkd.in/dPmFU2bR
#probabilistic #systems #AI #robotics
#probabilistic #systems #ai #robotics
The Sources Of Sea-Level Changes In The Mediterranean Sea Since 1960
--
https://doi.org/10.1029/2022JC019061 <-- shared paper
--
KEY POINTS:
• The average rate of sea-level rise in the Mediterranean Sea increased from −0.3 mm yr−1 in the period 1960–1989 to 3.6 mm yr−1 in 2000–2018
• Sterodynamic and land-mass changes both have made comparable contributions to the Mediterranean sea-level rise since 2000
• Since 2000, sea level has been rising faster in the Adriatic, Aegean, and Levantine Seas than anywhere else in the Mediterranean Sea…”
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#GIS #spatial #mapping #Mediterranean #climatechange #SLR #sealevelrise #model #modeling #remotesensing #history #change #trends #satellite #altimetry #tideguages #gauges #hydrography #hydrospatial #spatialanalysis #probabilistic #Baysean #glacier #melting
#gis #spatial #mapping #mediterranean #climatechange #slr #sealevelrise #model #modeling #remotesensing #history #change #trends #satellite #altimetry #tideguages #gauges #hydrography #hydrospatial #spatialanalysis #probabilistic #baysean #glacier #melting
I will have an open #internship position @AaltoUniversity on #probabilistic #circuits.
The internship will be within Aalto's #AScI program, which is an excellent opportunity! See project 4116 in the announcement below.
#internship #probabilistic #circuits #asci #machinelearning
Hello World!
I'm a Prof. of #ComputerScience at VRAIN/UPV (València, Spain), mainly working on (explainable, symbolic) artificial #intelligence #AI #XAI, (#probabilistic) #logic #programming, term #rewriting, #causality, #concurrency, programming #languages, #reversible computing, program #verification, and #debugging.
I plan to use this account mostly for scientific matters, but not only. I'm also quite interested in #photography, #sciencefiction, #travel, #movies, #series, etc, etc.
#computerscience #intelligence #ai #xai #probabilistic #logic #programming #rewriting #causality #concurrency #languages #reversible #verification #debugging #photography #sciencefiction #travel #movies #series
Online seminar TODAY:
💡 Score-based Generative Models on Riemannian manifolds
👨🔬 Emile Mathieu @mathieuemile@twitter.com
🗓️ Thursday Dec. 15, 15:00 EET
🔗 https://aaltoml.github.io/apml/
cc @trappmartin
#probabilistic #machinelearning
#machinelearning #probabilistic
#UAI is likely the best conference for #probabilistic #modeling #learning and #reasoning.
Consider submitting to #UAI2023
📆Deadline: 17 Feb AOE
#uai #probabilistic #modeling #learning #reasoning #uai2023
Online seminar next week:
💡 Score-based Generative Models on Riemannian manifolds
👨🔬 Emile Mathieu @mathieuemile@twitter.com
🗓️ Thursday Dec. 15, 15:00 EET
🔗 https://aaltoml.github.io/apml/
cc @trappmartin
#probabilistic #machinelearning
#machinelearning #probabilistic
Anyone out there using #probabilistic graphical models, #bayesian networks or the like for #decision making? I'm looking for a #tutor.
#probabilistic #bayesian #decision #tutor
Are you working on #Stochastic #Dynamics, #Uncertainty #Quantification or #Probabilistic #MachineLearning in the #EarthSciences ?
Consider submitting an abstract to our #EGU23 session:
https://meetingorganizer.copernicus.org/EGU23/session/45658
#atmosphere #ocean #cryosphere #solidearth
#hydrologicalcycle #biogeochemicalcycles #climate #nonlineardynamics
#EGU #nonlineardynamics #Climate #biogeochemicalcycles #hydrologicalcycle #solidearth #cryosphere #ocean #atmosphere #EGU23 #EarthSciences #machinelearning #probabilistic #quantification #uncertainty #dynamics #stochastic
Today I feel privileged to see my #ERCStG proposal
#UNREAL - A Unified Reasoning Layer for Trustworthy #ML
being funded by #ERC!
I will be working on #probabilistic #reasoning and #programming to #automate #realiable model design & deployment.
But first a big thanks to #friends and #colleagues who supported me through all the stages of the #ERCStG process, including:
#realiable #friends #colleagues #ercstg #unreal #ml #erc #probabilistic #reasoning #programming #automate
How?
SPLs realize a #tractable product of #experts via 2 #circuits.
One encodes an #expressive distribution over the labels, the other compactly #compiles the #symbolic #constraint!
We can compute #exact #gradients because we can normalize them in one feedforward pass!
This can be of interest to many #probabilistic folks!
cc @nbranchini @avehtari @PhilippHennig
5/
#constraint #exact #gradients #probabilistic #tractable #experts #circuits #expressive #compiles #symbolic
Our #Semantic #Probabilistic #Layers #SPLs instead always guarantee 100% of the times that predictions satisfy the injected constraints!
They can be readily used in deep nets as they can be trained by #backprop and #maximum #likelihood #estimation.
4/
#likelihood #estimation #semantic #probabilistic #layers #SPLS #backprop #maximum
#Probabilistic #modeling in biology follows from the insistence that #matter cannot have #history.
#probabilistic #modeling #matter #History
FCAI researchers on Mastodon (that we know of) are on this list.
https://mastodon.online/lists/2606
Toot away with @samikaski @oulasvirta @SimoSarkka @avehtari
@TeemuRoos @AcerbiLuigi
@HannuToivonen@mastodon.social (tai suomeksi @HannuToivonen@mastodontti.fi )
#artificialintelligence #machinelearning #probabilistic #ai #research #bayesian #tekoäly #koneoppiminen #tutkimus #finland
#finland #tutkimus #koneoppiminen #tekoaly #bayesian #research #ai #probabilistic #machinelearning #artificialintelligence
Now Chris Williams is presenting a principled probabilistic way to train #capsule networks (originally by @geoffreyhinton
) as generative models.
A variational approach to train generative part-based generative models.
#capsule #anc #seminar #ml #ai #probabilistic #generative #modeling