Top Tweets for #Normalizingflows
Next seminar (Tue, Jan 27): Manon Michel (CNRS, Univ. Clermont-Auvergne) “Harnessing Newtonian dynamics in generative models”. How laws of motion can make normalizing flows faster, cheaper, and more stable in high dimensions. #GenerativeModels #NormalizingFlows #MachineLearning
Robust Reconstruction of the Void Fraction from Noisy Magnetic Flux Density Using Invertible Neural Networks
https://t.co/u7emkbcdcO
@tudresden_de
#machinelearning; #invertibleneuralnetworks; #normalizingflows
Great new work by @Alegendree @RickyTQChen @RoVargasHdz @McMasterCCB @AIatMeta @BIMR_McMaster - 'Leveraging #normalizingflows for orbital-free density functional theory' - https://t.co/aYUycForTv #machinelearning #electronicstructure #compchem #DFT #materials #condmat #AI
Great new work by @GiulioBiroli @LudovicBerthie1 @CNRSphysique @ESPCI_Paris @LP_ENS_ @Physique_ENS @liphy_lab - '#Normalizingflows as an enhanced sampling method for #atomistic supercooled #liquids' - https://t.co/RCybPydsHI #machinelearning #statphys #glasses #softmatter #AI
🔉
Check out the camera ready version of the #ICLR2024 paper by @LVaitl @ludiXIVwinkler @lorenz_richter and @daspantom in collaboration with @bifoldberlin @ZuseInstitute @dida_ML and @PrescientDesign!
#MachineLearning #NormalizingFlows
We're excited to present our paper "Fast and Unified Path Gradient Estimators for Normalizing Flows" at #ICLR2024 in two weeks! 🎉 This work focuses on deriving efficient gradient estimators for coupling-type normalizing flows using the inverse function theorem.
Are you interested to learn what #NormalizingFlows can do for #ParticlePhysics? Join us on zoom this Thursday, 28.3., for a #COMETA WG2 meeting on "Normalizing Flows for HEP". We'll start at 10am CET. More infos: https://t.co/0QSsm4Mx4R
@multibosons spread the news!
Pre Christmas #HEPML papers, part 3
Together with Ben Nachman (@BPNachman), Ian Pang, David Shih, and Yunhao Zhu, we wondered:
When you learn to simulate #CalorimeterShowers with #NormalizingFlows, what else can you do with the likelihood of showers that you now have access to?
Pre Christmas #HEPML papers, part 2.
Together with Florian Ernst, Luigi Favaro, Tilman Plehn, and David Shih, we investigate how we can go beyond CaloFlow and scale #NormalizingFlows up to high-dimensional #Calorimeter data, while still being really fast in generation.
1/5
Great new work by @jmgduarte @rkansal47 @Mary_Touranakou et al @Unesp_Oficial @UCSDPhysics @UCSanDiego @CMSExperiment @CERN @DataSciSchools @dit_uoa @uoaofficial - '#LHC hadronic jet generation using convolutional variational ##autoencoders with #normalizingflows' - https://t.co/RTPOMoH3RG #machinelearning #HEP #particlephysics #AI #jets #collisions
Great new work by @PeteWirnsberger Borja Ibarz and @gpapamak @IsomorphicLabs @GoogleDeepMind - 'Estimating #Gibbs free energies via isobaric-isothermal flows' - https://t.co/5UQVxZDoK0 #machinelearning #statphys #AI #compchem #molecules #normalizingflows #moleculardynamics
Great new work by @eyal8615 and Daniel Freedman @Verily - 'Semi-equivariant conditional #normalizingflows, with applications to target-aware molecule generation' - https://t.co/DOxLIP7I1i #machinelearning #AI #graphs #neuralnetworks #compchem #molecules #quantum
🚨🚨🚨 🚨🚨🚨
Yesterday at the #LATTICE conference we presented NeuLat, a software package for flow-based sampling of LFT.
Check out this link if you want to know more https://t.co/cTehwgH1SR
Otherwise just reach out!✋🏻
#LATTICE23 #Fermilab #normalizingflows #sampling #NeuLat
2nd day of @EctTrento #ML & #lattice #fieldtheory workshop kicks off with a talk by Yukari Yamauchi @UW (Institute for Nuclear Theory) on a complex generalization of #normalizingflows. Converting a #signproblem laden complex distribution into a real Gaussian. #womeninphysics
👀 Curious about how to answering causal queries of mixed-type data?
🎯 Don't miss our latest work! We provide an answer to such question and much much more!
🧵Check out the amazing thread by @javaloyML
#NormalizingFlows #CausalInference
Hi! I am happy to announce our latest work (with @ML_pablosm and @IValeraM) ... 🥁
🚨 Causal normalizing flows: from theory to practice 🚨
I am really excited about this work! Check this image, and scroll down if you want to know more 👀
1/10
Replica exchange is a popular method for improving sampling in #MolecularDynamics. #NormalizingFlows are a promising deep generative method. Their combination can reduce the computational cost of both by orders of magnitude! @inve_michele @FrankNoeBerlin
https://t.co/9RKRN3G29H
We're happy to share that @TmlrOrg recently accepted our paper on "Efficient CDF Approximations for Normalizing Flows" by Chandramouli Sastry, Andreas Lehrmann, @marcusabrubaker and @Alex_Radovic. You can read it here: https://t.co/B4HHtW3MxP.
#CDF #normalizingflows #ML
Super proud of my good friend Lorenz for his first 1st author paper! and what a paper!!!😃 #NormalizingFlows #Oral #ICML2022
Did you know you can improve the training of your reparametrized generative model using a doubly reparametrized gradient estimator?
Here is a short thread for our #ICML2022 paper that develops an efficient algorithm for using these estimators for Continuous Normalizing Flows.
🚨 Principal component density estimation for scenario generation using normalizing flows
Cramer, @AlexanderMitsos, Tempone, Dahmen
→https://t.co/VhLjj3f15Q
#DimensionalityReduction #NormalizingFlows #PrincipalComponentAnalysis #RenewableEnergy #ScenarioGeneration #Renewables
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