On the Hardness of Conditional Independence Testing In Practice #3312, Thu 11am ✨spotlight✨
Doubly-Robust Estimation of Counterfactual Policy Mean Embeddings #2406, Fri 11am
Density Ratio-Free Doubly Robust Proxy Causal Learning #2413, Fri 11am
2/2
At #NeurIPS ? Visit our posters! 🧵
Demystifying Spectral Feature Learning for Instrumental Variable Regression: #2600, Wed 11am
Regularized least squares learning with heavy-tailed noise is minimax optimal: #3012, Wed 4:30pm ✨spotlight✨
1/2
🔥 WANTED: Student Researcher to join me, @vdebortoli.bsky.social, Jiaxin Shi, Kevin Li and @arthurgretton.bsky.social in DeepMind London.
You'll be working on Multimodal Diffusions for science. Apply here google.com/about/career...
Looking forward to next week's Winter School on Causality and Explainable AI!
xai-winter-school.github.io
Hope to see you there!
Fantastic news, congratulations!!
Thank you for a fantastic conference!
Sequential kernel embedding for mediated and time-varying dose response curves
Appearing in Bernoulli:
projecteuclid.org/journals/ber...
with preprint here: arxiv.org/abs/2111.03950
...along with code!
github.com/liyuan9988/K...
Rahul Singh, Liyuan Xu
Research Fellow position open at @gatsbyucl.bsky.social
to work with me and Jason Hartford on Causality in Biological Systems!
Apply at link, deadline is 27 August:
www.ucl.ac.uk/work-at-ucl/...
The method accepts draft proposals sequentially - once a proposal is rejected, a maximal coupling is used to obtain a valid sample, and the process repeats.
re "still working with kernels" - see the other ICML 2025 paper, arxiv.org/abs/2502.02483 which uses distributional kernel scoring rules!
Accelerated Diffusion Models via Speculative Sampling, at #icml25 !
16:30 Tuesday July 15 poster E-3012
arxiv.org/abs/2501.05370
@vdebortoli.bsky.social Galashov @arnauddoucet.bsky.social
Distributional diffusion models with scoring rules at #icml25
Fewer, larger denoising steps using distributional losses!
Wednesday 11am poster E-1910
arxiv.org/pdf/2502.02483
@vdebortoli.bsky.social
Galashov Guntupalli Zhou
@sirbayes.bsky.social
@arnauddoucet.bsky.social
Distributional Reduction paper with H. Van Assel, @ncourty.bsky.social, T. Vayer , C. Vincent-Cuaz, and @pfrossard.bsky.social is accepted at TMLR. We show that both dimensionality reduction and clustering can be seen as minimizing an optimal transport loss 🧵1/5. openreview.net/forum?id=cll...
Composite Goodness-of-fit Tests with Kernels, now out in JMLR!
www.jmlr.org/papers/v26/2...
Test if your distribution comes from ✨any✨ member of a parametric family. Comes in MMD and KSD flavours, and with code.
@oscarkey.bsky.social @fxbriol.bsky.social Tamara Fernandez
Turns out that overfitting is the right approach when you want to generalize to new tasks!
Mattes Mollenhauer, Nicole M\"ucke, Dimitri Meunier, Arthur Gretton: Regularized least squares learning with heavy-tailed noise is minimax optimal https://arxiv.org/abs/2505.14214 https://arxiv.org/pdf/2505.14214 https://arxiv.org/html/2505.14214
Looking forward to this!
Kernel Single Proxy Control for Deterministic Confounding
at #AISTATS25
Proxy causal learning generally requires two proxy variables - a treatment and an outcome proxy. When is it possible to use just one?
arxiv.org/abs/2308.04585
Liyuan Xu
Credal Two-Sample Tests of Epistemic Uncertainty
at #AISTATS25
Compare credal sets: convex sets of prob measures where elements capture aleatoric uncertainty; set represents epistemic uncertainty.
arxiv.org/abs/2410.12921
@slchau.bsky.social Schrab @sejdino.bsky.social @krikamol.bsky.social
Spectral Representation for Causal Estimation with Hidden Confounders
at #AISTATS2025
A spectral method for causal effect estimation with hidden confounders, for instrumental variable and proxy causal learning
arxiv.org/abs/2407.10448
Haotian Sun, @antoine-mln.bsky.social, Tongzheng Ren, Bo Dai
Density Ratio-based Proxy Causal Learning Without Density Ratios 🤔
at #AISTATS2025
An alternative bridge function for proxy causal learning with hidden confounders.
arxiv.org/abs/2503.08371
Bozkurt, Deaner, @dimitrimeunier.bsky.social, Xu
Announcing : The 2nd International Summer School on Mathematical Aspects of Data Science
mathsdata2025.github.io
EPFL, Sept 1–5, 2025
Speakers:
Bach @bachfrancis.bsky.social
Bandeira
Mallat
Montanari
Peyré @gabrielpeyre.bsky.social
For PhD students & early-career researchers
Apply before May 15!
Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression
#ICLR25
openreview.net/forum?id=ReI...
NNs
✨better than fixed-feature (kernel, sieve) when target has low spatial homogeneity,
✨more sample-efficient wrt Stage 1
Kim, @dimitrimeunier.bsky.social, Suzuki, Li
Deep MMD Gradient Flow Without Adversarial Training
at #ICLR2025
openreview.net/forum?id=Pf8...
Do you have a GAN critic? Then you have a diffusion!
Adaptive MMD gradient flow trained on a forward diffusion, competitive performance on image generation!
Galashov, @vdebortoli.bsky.social
Looking forward to this!
congratulations!!
Our joint paper with Geoffrey Wolfer @gwolfer.bsky.social "Variance-Aware Estimation of the Kernel Mean Embedding" accepted for publication in the Journal of Machine Learning Research 🥳
arxiv.org/abs/2210.06672
Congratulations @lestermackey.bsky.social !!
Hey ELLIS PhD students, need to travel but low on funds? Learn how ELSA can help with that: bit.ly/4kqjyel
#ELLISPhD #MobilityFund #SustainableAI #ProjectsBuildingOnELLIS
I already advertised for this document when I posted it on arXiv, and later when it was published.
This week, with the agreement of the publisher, I uploaded the published version on arXiv.
Less typos, more references and additional sections including PAC-Bayes Bernstein.
arxiv.org/abs/2110.11216