Top Tweets for #VariationalInference
Our first seminar of 2026 is coming up! 🎉
Tue, Jan 13: Bohan Wu (Columbia University) will speak on “Stability, instability, and extension of variational inference.” Zoom link on the seminar page. #VariationalInference #MCMC #Bayesian #OptimalTransport
Ovo ide: Part V published.
Variational inference is powerful—but not everything attributed to learning, memory, or structural change follows from its formalism.
This synthesis makes those boundaries explicit.
https://t.co/ZSR9IAk90r
#VariationalInference #ActiveInference
🙌New #SpecialIssue "Statistical Inference: Theory and Methods" edited by Prof. Michel Broniatowski, is Open for Submission!
➡️Submit to the Special Issue: https://t.co/UeNHiLpKfw
📅Submission deadline: 31 October 2025
#VariationalInference
#BayesianInference
#MachineLearning
"Navigating uncertainty in an efficient way: the negative of ELBO is known as variational free energy in neuroscience."
Artem Kirsanov
Explore how Variational Inference and ELBO enable intelligent systems to model probability distributions tractably.
#VariationalInference #ELBO #ProbabilityModeling #Neuroscience
https://t.co/smGtRJcHQx
📯 Check out the new publication!
Sparse #Bayesian #NeuralNetworks: Bridging Model and Parameter Uncertainty through Scalable #VariationalInference
https://t.co/61GBpssxwE
#BNNs #modelselection #predictiveuncertainty
#MDPIOpenAccess @ComSciMath_Mdpi
#Phd Thesis now in NOVA
Happy Thesis Thursday!
State and parameter estimation for nonlinear state-space models using variational inference (2021) https://t.co/yJRYqBUSps
#BayesianInference #NonlinearModels #VariationalInference
@arxiv @TUChemnitz @TUBerlin (2/6) In #VariationalInference & #GenerativeModeling, minimizing f-divergences is key (e.g. #KL, or Jensen-Shannon divergence in Minimax-#GAN). Since f-divergence between measures with disjoint support is infty, we regularize with a squared MMD induced by a characteristic kernel.
#mdpientropy #topcitedpaper: "Variational Message Passing and Local Constraint Manipulation in Factor Graphs" by İsmail Şenöz et al.
https://t.co/usEW2HXOpA
#Bayesianinference
Bethe #freeenergy
#factorgraphs
#messagepassing
#variationalinference
Careless, a program for scaling diffraction data using the Bayesian optimization method variational inference, is introduced and is contrasted with historical scaling algorithms @harvard @IUCr #XRayCrystallography #Scaling #VariationalInference https://t.co/F6j3mBz5lz
New episode is out! All about #MCMC & #VariationalInference
Enjoy, and get in touch for any feedback or suggestions ;)
Episode 90 with @charlesm993 is out!
We cover methods like variational inference & MCMC sampling and then dive into Charles' work in #pharmacometrics to see these methods applied!
We're also on Youtube now, in case you want to add a face to our voices: https://t.co/CmJAE0AczB
Luis A. Aldama et al.: Correcting systematic errors in diffraction data with modern scaling algorithms #XRayCrystallography #Scaling #VariationalInference @harvard... #IUCr https://t.co/FnCcyGmNbB
RT Variational Inference: The Basics #ai #machinelearning #variationalinference #bayesianstatistics https://t.co/YNjuPeIhJ8
For the #bayesian community, here a stack exchange post where clarifications are needed on variational bayes: https://t.co/QMCEpgyGFi
Any insights are welcomed
#variationalinference
Today we had our Third NeEDS Workshop On the Latest Advances in #MachineLearning to Deal with Complex Data at Copenhagen Business School
@needs_project @CBScph @CBS_ECON #XAI #orms #transparency #datadriven #decisionmaking #causalinference #spatialdata #variationalinference
1/n
RT An intuitive comparison of MCMC and Variational Inference https://t.co/0YeqVLSFUc #machinelearning #variationalinference #bayesianstatistics
For #machinelearning enthusiasts, a specially structured #variationalinference is used with cell state proportions as auxiliary variables ➕ a variational information bottleneck approach (PoE) for histology integration 💻 6/
deriving coordinate ascent variational inference (CAVI) updates is truly a pain in the ass...
#GraphicalModels #VariationalInference #MachineLearning
#variationalinference #technology #artificialintelligence Columbia U’s Infinitely Deep Probabilistic Model Adapts Its Complexity to the Data at Hand https://t.co/bv6au6ttDJ
Looking forward to attending (and speaking at) a workshop on Monte Carlo methods and approximate dynamic programming (variational inference) in Paris Aug. 25-26! #MonteCarlo #VariationalInference #Bayes #Statistics #DeepLearning #MachineLearning
https://t.co/LbWj8UXtot
Statistical and Computational Trade-offs in Variational Inference: A Case Study in Inferential Model Selection
Bhatia et al.: https://t.co/7xr4qH2HRg
#Artificialintelligence #DeepLearning #VariationalInference
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