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We develop a new approach for identifying and estimating average causal effects in panel data under a linear factor model with unmeasured confounders. Compared to other methods tackling factor models such as synthetic controls and matrix…

Methodology · Statistics 2021-08-10 Guido Imbens , Nathan Kallus , Xiaojie Mao

In the context of treatment effect estimation, this paper proposes a new methodology to recover the counterfactual distribution when there is a single (or a few) treated unit and possibly a high-dimensional number of potential controls…

Econometrics · Economics 2023-09-08 Ricardo Masini

We investigate a class of parametric elliptic semilinear partial differential equations of second order with homogeneous essential boundary conditions, where the coefficients and the right-hand side (and hence the solution) may depend on a…

Numerical Analysis · Mathematics 2025-05-13 Alexey Chernov , Tung Le

Proximal causal inference provides a framework for estimating the average treatment effect (ATE) in the presence of unmeasured confounding by leveraging outcome and treatment proxies. Identification in this framework relies on the existence…

Methodology · Statistics 2025-12-29 Chunrong Ai , Jiawei Shan

We give partial boundary regularity for co-dimension one absolutely area-minimizing currents at points where the boundary consists of a sum of $C^{1,\alpha}$ submanifolds, possibly with multiplicity, meeting tangentially, given that the…

Differential Geometry · Mathematics 2015-10-08 Leobardo Rosales

Model-based reinforcement learning is attractive for sequential decision-making because it explicitly estimates reward and transition models and then supports planning through simulated rollouts. In offline settings with hidden confounding,…

Machine Learning · Computer Science 2026-04-08 Nishanth Venkatesh , Andreas A. Malikopoulos

Contrasting marginal counterfactual survival curves across treatment arms is an effective and popular approach for inferring the causal effect of an intervention on a right-censored time-to-event outcome. A key challenge to drawing such…

Methodology · Statistics 2022-04-29 Andrew Ying , Yifan Cui , Eric J. Tchetgen Tchetgen

We give partial boundary regularity for co-dimension one absolutely area-minimizing currents at points where the boundary consists of a sum of $C^{1,\alpha}$ submanifolds, possibly with multiplicity, meeting tangentially, given that the…

Differential Geometry · Mathematics 2017-04-19 Leobardo Rosales

A quantitative regularity theory is developed for weak solutions to the parabolic system $$ \partial_t u-\mathrm{div}\,{\boldsymbol{\mathsf A}}(x,t,Du)=0 \quad\text{in }E_T\subset \mathbb{R}^N\times\mathbb{R}, $$ which features the…

Analysis of PDEs · Mathematics 2026-01-14 Verena Bögelein , Frank Duzaar , Ugo Gianazza , Naian Liao

A common concern when a policymaker draws causal inferences from and makes decisions based on observational data is that the measured covariates are insufficiently rich to account for all sources of confounding, i.e., the standard no…

Methodology · Statistics 2023-10-25 Tao Shen , Yifan Cui

In this article we show a $C^{0,\alpha}$-partial regularity result for solutions of a certain class of cross-diffusion systems with entropy structure. Under slightly more stringent conditions on the system, we are able to obtain a…

Analysis of PDEs · Mathematics 2022-04-14 Marcel Braukhoff , Claudia Raithel , Nicola Zamponi

Difference-in-differences (DiD) is a cornerstone of causal inference, yet extending it to functional outcomes is not a routine scalar generalization; rather, it entails three fundamental challenges in identification, inference, and…

Methodology · Statistics 2026-05-29 Junzhu Nie , Chengxiu Ling , Mengfei Ran

We study the Cauchy-Dirichlet problem associated to a phase transition modeled upon the degenerate two-phase Stefan problem. We prove that weak solutions are continuous up to the parabolic boundary and quantify the continuity by deriving a…

Analysis of PDEs · Mathematics 2017-02-24 Paolo Baroni , Tuomo Kuusi , Casimir Lindfors , José Miguel Urbano

In causal inference, an important problem is to quantify the effects of interventions or treatments. Many studies focus on estimating the mean causal effects; however, these estimands may offer limited insight since two distributions can…

Methodology · Statistics 2024-11-05 Archer Gong Zhang , Nancy Reid , Qiang Sun

In inverse problems, we often have access to data consisting of paired samples $(x,y)\sim p_{X,Y}(x,y)$ where $y$ are partial observations of a physical system, and $x$ represents the unknowns of the problem. Under these circumstances, we…

Machine Learning · Statistics 2020-07-17 Ali Siahkoohi , Gabrio Rizzuti , Philipp A. Witte , Felix J. Herrmann

We establish that the $C^{1,\gamma}$ regularity theory for translation invariant fractional order parabolic integro-differential equations (via Krylov-Safonov estimates) gives an improvement of regularity mechanism for solutions to a…

Analysis of PDEs · Mathematics 2020-08-28 Farhan Abedin , Russell W. Schwab

Convolution with an appropriate surface measure on a paraboloid is known to define a bounded operator T from L^p(R^d) to L^q(R^d) for certain exponents p,q. By a quasiextremal for the associated inequality, we mean a function f for which…

Classical Analysis and ODEs · Mathematics 2011-06-06 Michael Christ

In this contribution we obtain partial $C^{0,\alpha}$-regularity for bounded solutions of a certain class of cross-diffusion systems, which are strongly coupled, degenerate quasilinear parabolic systems. Under slightly more restrictive…

Analysis of PDEs · Mathematics 2021-12-30 Marcel Braukhoff , Claudia Raithel , Nicola Zamponi

Near the critical temperature of a superconducting transition, the energy of the threshold perturbation $\delta F_{thr}$ that transfers a superconducting bridge to a resistive state at a current below the critical current $I_c$ has been…

Superconductivity · Physics 2016-06-08 P. M. Marychev , D. Yu. Vodolazov

We study the statistical inference problem for a complex $\alpha$-fractional Brownian bridge process $Z$ defined by the stochastic differential equation \[ \mathrm{d}Z_t = -\alpha \frac{Z_t}{T - t} \mathrm{d}t + \mathrm{d}\zeta_t, \quad t…

Probability · Mathematics 2026-03-10 Yong Chen , Lin Fang , Ying Li , Hongjuan Zhou
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