Looking forward to next week's Winter School on Causality and Explainable AI!

xai-winter-school.github.io

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

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

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

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

"Learning to Act in Noisy Contexts Using Deep Proxy Learning"

Talk at the #NeurIPS2024 Causal Representation Learning Workshop neurips.cc/virtual/2024...

Sunday 15th December (tomorrow!), 8:45am, East Exhibition Hall C

Data balancing for fairness: when does it work? When does it not?

"Mind the Graph When Balancing Data for Fairness or Robustness"

#NeurIPS2024 West Ballroom A-D #5507
Fri 13 Dec 11 a.m. PST — 2 p.m. PST

neurips.cc/virtual/2024...

Distributional SFs: enable 0-shot generalization of return *distribution* functions across a finite-dimensional reward function class

"Foundations of Multivariate Distributional Reinforcement Learning"

#NeurIPS2024 #6704
12 Dec 11am-2pm
neurips.cc/virtual/2024...

Wiltzer Farebrother Rowland

Conditional mean embeddings without Tikhonov: no saturation effect!

"Optimal Rates for Vector-Valued Spectral Regularization Learning Algorithms"

#NeurIPS2024 Poster #5709
12 Dec 11 a.m.— 2 p.m

neurips.cc/virtual/2024...

Meunier, Shen, Mollenhauer, Li

Use contrastive divergence to learn energy-based models as well as with maximum likelihood!

"Near-Optimality of Contrastive Divergence Algorithms"
Pierre Glaser, Kevin Han Huang

at #NeurIPS2024
West Ballroom A-D #5609
Wed 11 Dec 4:30 — 7:30 p.m. PST

neurips.cc/virtual/2024...