The abstract submission deadline for the ELLIS Workshop on Amortized Probabilistic ML has been extended to October 25th!
You still have time to submit a short abstract on your work in: Amortized Inference, Neural processes, Prior-fitted networks, Sequential Decision-Making, and Foundation models.
17.10.2025 11:22 — 👍 8 🔁 6 💬 1 📌 0
“Collaboration is a feature of the Finnish research community” | ELLIS Institute Finland
Strong collegial network is an asset to Ayush Bharti's research on robust machine learning.
Thinking about a #PhD in AI + #machinelearning?
🇫🇮 Read about @ayushbharti.bsky.social's experience doing research in Finland:
www.ellisinstitute.fi/collaboratio...
Then,
👀 Apply for the @ellis.eu PhD program by October 31 🎃 : ellis.eu/news/ellis-p...
06.10.2025 11:06 — 👍 4 🔁 1 💬 0 📌 0
Doctoral Researcher (simulation-based inference) / Väitöskirjatutkija (simulaatio-pohjainen päättely)
I'm looking for a Doctoral Researcher (PhD student) to work with me on simulation-based inference at Data Science Research Centre, Tampere University Check the link for details and send an application before October 10th.
tuni.rekrytointi.com/paikat/?o=A_...
01.09.2025 06:51 — 👍 8 🔁 8 💬 0 📌 0
Just finished delivering a course on 'Robust and scalable simulation-based inference (SBI)' at Greek Stochastics. This covered an introduction to SBI, open challenges, and some recent contributions from my own group.
The slides are now available here: fxbriol.github.io/pdfs/slides-....
28.08.2025 11:46 — 👍 35 🔁 9 💬 1 📌 1
Great initiative!
03.07.2025 08:03 — 👍 2 🔁 0 💬 0 📌 0
Thank you so much! Glad you liked it.
02.05.2025 15:24 — 👍 0 🔁 0 💬 0 📌 0
Doing so saves hours of computation time for the radio propagation model without any degradation in performance. (5/5)
02.05.2025 06:45 — 👍 1 🔁 0 💬 0 📌 0
Sampling from the cost-aware proposal is done via rejection sampling, and self-normalised importance weights are used to target the SBI posterior. (4/5)
02.05.2025 06:45 — 👍 3 🔁 0 💬 1 📌 0
We propose to sample from a cost-aware proposal to encourage sampling from the cheaper parameterisations of the model. (3/5)
02.05.2025 06:45 — 👍 3 🔁 0 💬 1 📌 0
Oftentimes, this computational cost varies with the parameter value, as is the case with this model from wireless communications field where the cost increases linearly. (2/5)
02.05.2025 06:45 — 👍 1 🔁 0 💬 1 📌 0
Thread below:
Popular SBI methods such as Approximate Bayesian computation (ABC), neural posterior estimation (NPE) and neural likelihood estimation (NLE) require running the simulator thousands of times, which can be a computational bottleneck. (1/5)
02.05.2025 06:45 — 👍 1 🔁 0 💬 1 📌 0
Poster
02.05.2025 06:45 — 👍 2 🔁 0 💬 1 📌 0
Cost-aware simulation-based inference
Simulation-based inference (SBI) is the preferred framework for estimating parameters of intractable models in science and engineering. A significant challenge in this context is the large computation...
"Cost-aware simulation-based inference" is accepted at AISTATS 2025.
Check out our poster #205 on Sunday May 4th in Hall A-E if you are in Phuket. Finland's rising star @huangdaolang.bsky.social will be there to assist you :D
arxiv.org/abs/2410.07930
@fxbriol.bsky.social @samikaski.bsky.social
02.05.2025 06:45 — 👍 18 🔁 5 💬 2 📌 1
Looking forward to this!
23.04.2025 13:26 — 👍 0 🔁 0 💬 0 📌 0
Multi-Head Latent Attention vs Group Query Attention: We break down why MLA is a more expressive memory compression technique AND why naive implementations can backfire. Check it out!
12.03.2025 19:01 — 👍 25 🔁 10 💬 0 📌 1
Looking forward to speaking at the @approxbayesseminar.bsky.social!
14.02.2025 13:14 — 👍 6 🔁 0 💬 0 📌 0
Our next talk will be on Thursday the 27th February at 11am UK time. Our next speaker is Ayush Bharti (Aalto University), who will talk about "Cost-aware simulation-based inference". To receive the link, sign up here: listserv.csv.warwick...
14.02.2025 10:41 — 👍 11 🔁 5 💬 1 📌 1
Congrats 🎉
20.12.2024 16:35 — 👍 3 🔁 0 💬 0 📌 0
If you are interested in doing a #PhD with me at Imperial College London and qualify as a home student, please reach out (before end of 2024)! Potential topics: spatial statistics, applied deep generative models, probabilistic programming and more.
19.12.2024 14:21 — 👍 7 🔁 5 💬 0 📌 0
Congratulations Matias!
10.12.2024 14:17 — 👍 4 🔁 0 💬 0 📌 0
Optimizing decision utility in Bayesian experimental design is key to improving downstream decision-making.
Excited to share our #NeurIPS2024 paper on Amortized Decision-Aware Bayesian Experimental Design: arxiv.org/abs/2411.02064
@lacerbi.bsky.social @samikaski.bsky.social
Details below.
05.12.2024 12:18 — 👍 41 🔁 12 💬 1 📌 2
@huangdaolang.bsky.social just joined here and you should follow him if you are interested in probabilistic machine learning, (Bayesian) exp. design and AI-assisted decision making. Not to mention that he has *several* NeurIPS papers already while in his 3rd PhD year...
27.11.2024 15:30 — 👍 8 🔁 1 💬 0 📌 0
Looks very interesting. This goes to the top of my reading list 😀
21.11.2024 06:25 — 👍 2 🔁 0 💬 1 📌 0
Hi, I'd like to join if that's ok.
19.11.2024 09:16 — 👍 1 🔁 0 💬 0 📌 0
✋
19.11.2024 09:14 — 👍 0 🔁 0 💬 1 📌 0
Sure. Will do.
19.11.2024 09:09 — 👍 1 🔁 0 💬 0 📌 0
Thanks for creating this (and adding me) Marvin!
19.11.2024 07:59 — 👍 1 🔁 0 💬 1 📌 0
Associate Professor in Machine Learning, Aalto University. ELLIS Scholar.
http://arno.solin.fi
Professor of Computer Vision/Machine Learning at Imagine/LIGM, École nationale des Ponts et Chaussées @ecoledesponts.bsky.social Music & overall happiness 🌳🪻 Born well below 350ppm 😬 mostly silly personal views
📍Paris 🔗 https://davidpicard.github.io/
Team leader (tenured) at RIKEN AIP. Opinions my own. https://emtiyaz.github.io
🌉 bridged from https://mastodon.social/@emtiyaz on the fediverse by https://fed.brid.gy/
Department of Computer Science in Aalto University, Finland.
Meet our people & read more about our work at cs.aalto.fi.
Computer Scientist at SRI. Machine Learning. Uncertainty Quantification.
Postdoctoral researcher,
Human-in-the-loop Decision making
Aalto University, Finland
PhD: Inria Lille, France
Machine Learning@University of Bath, UK.
Posts about Bayesian statistics, Monte Carlo, etc from a Reader in Statistics at the University of Warwick https://bsky.app/profile/warwickstats.bsky.social. Personal account. https://richardgeveritt.github.io/
Tenured Asst Prof at the Uni Groningen, Uncertainty in Machine Learning, Robotics, Chilean, Photographer, Feminist, Snoopy lover, Dr #latinXinAI
A world-class research hub in AI and machine learning, in partnership with universities, RDI organizations and businesses in Finland. We are the 2nd institute in the @ellis.eu network.
🔗 ellisinstitute.fi
Assistant professor in applied statistics at Tampere University
Likelihood-free inference|Statistical modelling|Often Bayesian|Open source software development
Research Scientist GoogleDeepMind
Ex @UniofOxford, AIatMeta, GoogleAI
Postdoc at Aalto University in the Probabilistic ML Group
Associate Prof. in ML & Statistics at NUS 🇸🇬
MonteCarlo methods, probabilistic models, Inverse Problems, Optimization
https://alexxthiery.github.io/
Assistant Professor at the university of Warwick.
I compute integrals for a living.
https://adriencorenflos.github.io/
TMLR Homepage: https://jmlr.org/tmlr/
TMLR Infinite Conference: https://tmlr.infinite-conf.org/
PhD candidate @ University of Edinburgh
Bayesian Stats | Machine Learning | Uncertainty Quantification | ML4Science | Scientific Imaging
https://teresa-klatzer.github.io/
ML Research scientist. Interested in geometry, information theory and statistics 🧬
Opinions are my own. :)
Reader in Statistics at the University of Warwick | Inference for Stochastic processes | Simulation-based inference| Stochastic Numerics | Parallel-in-time numerical methods| Stochastic Modelling | Neuroscience | www.warwick.ac.uk/tamborrino
