David M. Knigge @davidmknigge
PhD candidate w/ @egavves at @uva_amsterdam medical and geometric deep learning. @ic4ai POP-AART Lab w/ @elekta & @NKI_nl. davidmknigge.nl Amsterdam Joined July 2022-
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📢#GRaM template for proceedings track is up on our website gram-workshop.github.io . Submit your great ideas in a #ICML like 8-page submission. Accepted papers will be published in PMLR ✨#GRaM proceedings ✨.
Reminder for tomorrow's tutorial on Subquadratic Long-Context models by @davidwromero! 📅 Thu, April 11th 09:00 - 11:00 📍 L1.01 at @Lab42UvA 🌐 zoom link at thedeepthinkinghour.github.io.
Reminder for tomorrow's tutorial on Subquadratic Long-Context models by @davidwromero! 📅 Thu, April 11th 09:00 - 11:00 📍 L1.01 at @Lab42UvA 🌐 zoom link at thedeepthinkinghour.github.io.
Will the future be dominated by transformers? @davidwromero (@nvidia) will talk about what is waiting for us beyond transformers at the upcoming Deep Thinking Hour 💭 Tutorial. 📅 Thu, April 11th 📍L1.01 (Science Park, Ams) Stream link will be at thedeepthinkinghour.github.io
🗓️ Reminder! @phillip_lippe's tutorial on training massive deep learning models is happening this afternoon at 17:00 CET in C0.110 SP904. Also live-streamed over zoom. For info and links: thedeepthinkinghour.github.io ✨
🗓️ Reminder! @phillip_lippe's tutorial on training massive deep learning models is happening this afternoon at 17:00 CET in C0.110 SP904. Also live-streamed over zoom. For info and links: thedeepthinkinghour.github.io ✨
Our work got published in Machine Learning: Sci & Tech! 🎉 @egavves @MLSTjournal We propose a method for encoding complicated symmetries pervasive in scientific data, apply it to neural symmetry detection AND argue for more diverse PDE datasets! (1/n) iopscience.iop.org/article/10.108…
🔈The @UvA_Amsterdam and @ELLISforEurope are hosting a tutorial on "Training Models at Scale 🔥" in Ams on March 11th at 17:00 CET (streaming will be posted on thedeepthinkinghour.github.io). Come with us to explore strategies to train massive models with @phillip_lippe.
Does your research involve fitting / processing / using Neural Fields and find that the your bottleneck is fitting the Neural Fields themselves? Here's the solution to your problems! Great effort! 😍 Congrats to the team! 💪
Does your research involve fitting / processing / using Neural Fields and find that the your bottleneck is fitting the Neural Fields themselves? Here's the solution to your problems! Great effort! 😍 Congrats to the team! 💪
🎉 Our paper "How to Train Neural Field Representations" (fit-a-nef.github.io) has been accepted at #CVPR2024! Grateful to the team @RValperga @davidmknigge @MiltosKofinas @phillip_lippe and supervisors @Efstratios and Jan-Jakob Sonke!🙌 (1/4)
Glad we were able to accept so many great papers to our workshop this year! 😄 @MajiSubhransu @erikjbekkers @compute_ri @davidmknigge @LorenzoBrigato @AttilaLengyel8 @OmbrettaSt and many others! See you all in Paris!! #ICCV2023
Glad we were able to accept so many great papers to our workshop this year! 😄 @MajiSubhransu @erikjbekkers @compute_ri @davidmknigge @LorenzoBrigato @AttilaLengyel8 @OmbrettaSt and many others! See you all in Paris!! #ICCV2023
Sindy Löwe @sindy_loewe
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8K Followers 9K Following Senior functional/technical consultant to bring added value via #digitalhealth #ai and #datascience based solutions #MedTwitterPaul @paulhausner
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39K Followers 7K Following I lead @CohereForAI. Formerly Research @Google Brain @GoogleDeepmind. ML Efficiency at scale, LLMs, @trustworthy_ml. Changing spaces where breakthroughs happen.Zhaoyang Wang @wangwan83764204
309 Followers 4K Following CS PhD student at UoB in the United Kingdom. Research interests: Automated Machine Learning, Online Learning, and Reinforcement Learning 🏳️🌈Sindy Löwe @sindy_loewe
3K Followers 360 Following PhD Student with @WellingMax at the University of Amsterdam. Deep Learning with Structured Representations.Max Welling @wellingmax
32K Followers 432 FollowingEfstratios Gavves @egavves
2K Followers 562 Following Associate Professor & Co-Founder - Temporal Learning & Neural DynamicsYuki @y_m_asano
3K Followers 683 Following Assistant Professor for Computer Vision and Machine Learning at the QUVA Lab, @UvA_Amsterdam. Previously @Oxford_VGG, @OxfordAI, interned @facebookaiTaco Cohen @TacoCohen
21K Followers 3K Following Deep learner at FAIR. Into codegen, equivariance, generative models. Spent time at Qualcomm, Scyfer (acquired), UvA, Deepmind, OpenAI.Symmetry and Geometry.. @neur_reps
3K Followers 1K Following NeurIPS workshop and digital community | 🌐 geometry, algebra, topology + 🤖 deep learning + 🧠 neuroscience | Join us on slack! https://t.co/Run9wPnZt9Sharvaree Vadgama @SharvVadgama
831 Followers 2K Following PhD student at @AmlabUva with @erikjbekkers & @jmtomczak | everything Geometric + Generative models | MS CS @UUtah | Theoretical Physics @IISERPune | she/herELLIS Amsterdam @Ellis_Amsterdam
1K Followers 258 Following Twitter account of the ELLIS Amsterdam Unit. Promoting research excellence and advancing breakthroughs in AI. Maintainers: @pranindiati, @cgmsnoek, @adi_sauterErik Bekkers @erikjbekkers
4K Followers 856 Following Assis. Prof @AmlabUva @UvA_Amsterdam @Ellis_Amsterdam | @ELLISforEurope Scholar | Geometric and Group Equivariant Deep Learning | IdealistYann LeCun @ylecun
711K Followers 718 Following Professor at NYU. Chief AI Scientist at Meta. Researcher in AI, Machine Learning, Robotics, etc. ACM Turing Award Laureate.Johannes Brandstetter @jo_brandstetter
3K Followers 620 Following Ass. Prof / Group Lead @jkulinz, Head of Research - AI4Simulation NXAI. Former @MSFTResearch, @UvA_Amsterdam, @CERN, @tu_wienMelika Ayoughi @melikaayoughi
477 Followers 238 Following Ph.D. Candidate at the University of Amsterdam at VISLab @UvA_Amsterdam & @INDE_LAB_AMSMichael Bronstein @mmbronstein
43K Followers 4K Following #DeepMind Professor of #AI @UniofOxford / Fellow @ExeterCollegeOx / ML Lead @ProjectCETI / https://t.co/kZpGpDzYeVSara Magliacane (she/.. @saramagliacane
3K Followers 1K Following Assistant professor @AmlabUva @UvA_Amsterdam & Research Scientist @MITIBMLab , #causality #CausalRepresentationLearning #causalityInspiredML, 🇮🇹🇸🇮 in 🇳🇱Kaitlin Maile @kaitlinmaile
417 Followers 584 Following PhD student @Univ_Toulouse. Architectural optimization for neural networks.Cees Snoek @cgmsnoek
4K Followers 2K Following Head of Video & Image Sense Lab | University of Amsterdam | Director @Ellis_Amsterdam | Scientific Director Amsterdam AIDavid Ruhe @djjruhe
1K Followers 394 Following Student Researcher @GoogleDeepMind ; PhD Candidate Machine Learning @AmlabUva, @ai4science_lab @UvA_Amsterdam. Previously @MSFTResearch, @FlatironInstPetar Veličković @PetarV_93
30K Followers 555 Following Staff Research Scientist @GoogleDeepMind | Affiliated Lecturer @Cambridge_Uni | Associate @clarehall_cam | GDL Scholar @ELLISforEurope. Monoids. 🇷🇸🇲🇪🇧🇦Andy Keller @t_andy_keller
2K Followers 933 Following Postdoctoral Fellow at The Kempner Institute at Harvard University -- Somewhere between Brains & Bits. PhD at UvA, Intern @ Apple MLR, Prev @ Intel AI & NervanaElise van der Pol @ElisevanderPol
3K Followers 508 Following Senior Researcher at Microsoft Research Amsterdam. Structure, symmetry and equivariance in RL and AI4Science. She/her.Gram Workshop @GRaM_workshop
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426 Followers 727 Following Working on Visual Language models | PhD candidate @UvA_Amsterdam | ML/CV Intern @ Microsoft Research | EX-ML/CV Intern @ Samsung AI CambridgeTim Bakker @timbbakker
589 Followers 390 Following PhD ML with Max Welling at UvA. Active learning/sensing, EA, and everything Bayesian. Sings a lot. Speaker on (existential) risks from AI.Michael Dorkenwald @mdorkenw
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1K Followers 447 Following Final-year AI PhD student @Stanford. NN architecture design, learned optimizers, and hparam optimization.Vincent Sitzmann @vincesitzmann
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27K Followers 452 Following Digital Geometer, Assoc. Prof. of Computer Science & Robotics @CarnegieMellon @SCSatCMU and member of the @GeomCollective. https://t.co/edHwujkFsASubmit your brilliant new ideas to our workshop proceedings track. #GRaM workshop at #ICML2024
📢#GRaM template for proceedings track is up on our website gram-workshop.github.io . Submit your great ideas in a #ICML like 8-page submission. Accepted papers will be published in PMLR ✨#GRaM proceedings ✨.
📢#GRaM template for proceedings track is up on our website gram-workshop.github.io . Submit your great ideas in a #ICML like 8-page submission. Accepted papers will be published in PMLR ✨#GRaM proceedings ✨.
This was an outstanding and inspiring lecture by @davidwromero ! If you want to get up to speed with SSMs / long-conv models (CKConv, Hyena, Mamba, etc) —which beat transformers, please watch back the recordings! My take-home as usual is: convolution is all you need! 🙃
I am very happy to give this tutorial next week! We will discuss several developments on sub-quadratic long-context architectures such as SSMs, CKConv, Hyena and Mamba. Thank you @Ellis_Amsterdam for having me!
Let's learn together about this exciting research field! :D
Reminder for tomorrow's tutorial on Subquadratic Long-Context models by @davidwromero! 📅 Thu, April 11th 09:00 - 11:00 📍 L1.01 at @Lab42UvA 🌐 zoom link at thedeepthinkinghour.github.io.
Research Internship Alert! 🚨 Are you interested in SSMs / long-conv models (CKConv, Hyena, Mamba, etc) and their role in #GenerativeAI? Join our team and get involved in groundbreaking efficient GenAI research! Intrigued? 🤔 Reach out via DM or email at [email protected]
One more sleep until the Deep Thinking Hour Tutorial tomorrow morning 💥 *☕️ & 🍰 will be provided
Reminder for tomorrow's tutorial on Subquadratic Long-Context models by @davidwromero! 📅 Thu, April 11th 09:00 - 11:00 📍 L1.01 at @Lab42UvA 🌐 zoom link at thedeepthinkinghour.github.io.
Will the future be dominated by transformers? @davidwromero (@nvidia) will talk about what is waiting for us beyond transformers at the upcoming Deep Thinking Hour 💭 Tutorial. 📅 Thu, April 11th 📍L1.01 (Science Park, Ams) Stream link will be at thedeepthinkinghour.github.io
Excellent closing of @ecir2024. Great tutorial on Transformers for RecSys by @craig_macdonald and @asash. Thank you guys!
Also, @ecir2024 is a great intro to the IR community for me so far. Enjoying being in Scotland for a while too!
Totally agree with Mohammad! Got to introduce a short discussion myself on whether or not we should use LLMs for a nuanced and sensitive topic like normative diversity.
In love with the Search Futures workshop @ecir2024 . Lots of interesting questions and ideas discussed so far. @simon_lupart is now sharing his thoughts on generative conversational IR. #ECIR2024
Happy to have shared our recent work fit-a-nef.github.io at the ELLIS Winter School on Foundation Models @Ellis_Amsterdam some great discussions and excellent preparation for CVPR 🤓 #ELLIS
Houston, we have a liftoff. #ELLIS Unit #Amsterdam presents the Winterschool on #Foundation #Models. 150 talents from 90 institutions and 40 nationalities. w/ @y_m_asano
Implicit steerable kernels are taking off! 🚀 We significantly simplified the code and now support steerable convolutions on both regular and irregular grids! 🛠️Code: github.com/maxxxzdn/impli… 🗒️ Google Colab tutorial: colab.research.google.com/drive/1mE_9GRW… 🧵1/8
We proudly present our 524 page book on equivariant convolutional networks. Coauthored by Patrick Forré, @erikverlinde and @wellingmax. maurice-weiler.gitlab.io/#cnn_book [1/N]
Like to work on cutting edge generative AI using physics tools such as the Renormalization Group, with the briliant mathematician & physicist prof Miranda Cheng at U. Amsterdam (co-supervised by me)? Think no more and apply to below! academicjobsonline.org/ajo/jobs/27314
We also propose using a suite of 25 PDEs labeled by their non-canonical symmetries for experimenting with neural symmetry detection beyond rotation, scaling and translation! (n/n) And, of course, big thanks to my supervisors Stratis Gavves and Rick Quax here at @UvA_Amsterdam!
In a straightforward experiment, we show how symmetry detection can be done for PDE data using this encoding. In some cases, parts of correct symmetry transformations were identified when applied to unseen dynamics 👉 Exciting possibility for further work! (3/n)
Our proposed encoding takes symmetry transformations that map solutions of a given PDE to other solutions and stores the normalized coefficients of the associated vector field defining its flow in solution space (2/n)
Our work got published in Machine Learning: Sci & Tech! 🎉 @egavves @MLSTjournal We propose a method for encoding complicated symmetries pervasive in scientific data, apply it to neural symmetry detection AND argue for more diverse PDE datasets! (1/n) iopscience.iop.org/article/10.108…