A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.
Machine learning improves kidney transplant outcomes prediction.
Paper learns data-driven organ matching rules from observational data.
The burgeoning need for kidney transplantation mandates immediate attention. Mismatch of deceased donor-recipient kidney leads to post-transplant death. To ensure ideal kidney donor-recipient match and minimize post-transplant deaths, the paper develops a prediction model that identifies factors that determine the prob…
Background: Many authors have described MELD as a predictor of short-term mortality in the liver transplantation waiting list. However MELD score accuracy to predict long term mortality has not been statistically evaluated. Objective: The aim of this study is to analyze the MELD score as well as other variables as a pr…
John Conway created pairs of domains that sound the same for a special kind of music.
Local discovery method uncovers direct unfairness in complex systems.
We study isospectrality for manifolds with mixed Dirichlet-Neumann boundary conditions and express the well-known transplantation method in graph- and representation-theoretic terms. This leads to a characterization of transplantability in terms of monomial relations in finite groups and allows for the generating of ne…
This paper focuses on a new task, i.e., transplanting a category-and-task-specific neural network to a generic, modular network without strong supervision. We design an functionally interpretable structure for the generic network. Like building LEGO blocks, we teach the generic network a new category by directly transp…
This paper focuses on a new task, i.e., transplanting a category-and-task-specific neural network to a generic, modular network without strong supervision. We design a functionally interpretable structure for the generic network. Like building LEGO blocks, we teach the generic network a new category by directly transpl…
We say that a germ G of a geometric structure can be transplanted into a manifold M if there is a suitable geometric structure on M which agrees with G on a neighborhood of some point P of M. We show for a wide variety of geometric structures that this transplantation is always possible provided that M does in fact adm…
25% of people who received a liver transplant will go on to develop diabetes within the next 5 years. These thousands of individuals are at 2-fold higher risk of cardiovascular events, graft loss, infections, as well as lower long-term survival. This is partly due to the medication used during and/or after transplant t…
Method learns evolving policies in healthcare contexts.
New method for finding optimal treatment regimes in medical settings with time-varying unobserved factors.
This paper presents the first deep reinforcement learning (DRL) framework to estimate the optimal Dynamic Treatment Regimes from observational medical data. This framework is more flexible and adaptive for high dimensional action and state spaces than existing reinforcement learning methods to model real-life complexit…
We prove that C. Loewner's inequality for the torus is satisfied by all hyperelliptic surfaces X, as well. We first construct the Loewner loops on the (mildly singular) companion tori, locally isometric to X away from the Weierstrass points. The loops are then transplanted to X, and surgered to obtain a Loewner loop on…
Electronic Health Records (EHRs) have been heavily used to predict various downstream clinical tasks such as readmission or mortality. One of the modalities in EHRs, clinical notes, has not been fully explored for these tasks due to its unstructured and inexplicable nature. Although recent advances in deep learning (DL…
Deep learning classifies keratoconus patients with high accuracy.
Proposes a neural network for dynamic risk prediction of AMD using longitudinal fundus images.
Introduction. Case Based Reasoning (CBR) is an emerg- ing decision making paradigm in medical research where new cases are solved relying on previously solved similar cases. Usually, a database of solved cases is provided, and every case is described through a set of attributes (inputs) and a label (output). Extracting…
New energy measure for isolated systems in general relativity.
Given a hyperelliptic Klein surface, we construct companion Klein bottles, extending our technique of companion tori already exploited by the authors in the genus 2 case. Bavard's short loops on such companion surfaces are studied in relation to the original surface so to improve a systolic inequality of Gromov's. A ba…
Although much progress has been made in classification with high-dimensional features \citep{Fan_Fan:2008, JGuo:2010, CaiSun:2014, PRXu:2014}, classification with ultrahigh-dimensional features, wherein the features much outnumber the sample size, defies most existing work. This paper introduces a novel and computation…
The paper examines how macroeconomic control tools lost effectiveness, leading to a 'dark ages' period.
This article considers the quasi-local conserved quantities with respect to a reference spacetime with a cosmological constant. We follow the approach developed by the authors in [25,26,7] and define the quasi-local energy as differences of surface Hamiltonians. The ground state for the gravitational energy is taken to…
In this paper, by extending the notions of harmonic transplantation and harmonic radius in the Heisenberg group, we give an upper bound for the first eigenvalue for the following Dirichlet problem: $$(P_Ω) \left\{ \begin{array}{lllll} -Δ_{\mathbb{H}^1} u & = & λu & \mbox{in} & Ωu & = & 0 & \mbox{on} & \partial Ω, \end{…
We describe in this talk three methods of constructing different links with the same Jones type invariant. All three can be thought as generalizations of mutation. The first combines the satellite construction with mutation. The second uses the notion of rotant, taken from the graph theory, the third, invented by Jones…
The paper proposes a method to infer multi-objective rewards from preferences.
Paper simplifies balancing weights by relaxing outcome assumptions.
A method corrects bias in estimating a high-dimensional classification rule using auxiliary outcomes.
PO-Flow models potential and counterfactual outcomes for personalized treatment decisions.
Fuses ITRs for primary and secondary outcomes to minimize harm.
Firms delay write-downs for adverse macroeconomic and industry outcomes but not for firm-specific issues.
Reduces variance in noisy social outcomes to improve policy evaluation and optimization.
The paper introduces metrics to rank potential outcomes for better decision-making.
Study dynamic matching in heterogeneous networks using ODE model.
Proposes a deep learning framework for estimating counterfactual outcomes.
The study uses transfer learning to compare surgical outcomes across racial/ethnic subgroups.
DEBIAS learns causal effects from psychiatric longitudinal data by optimizing outcome weights.
New approach tackles decision-making under predictions that shape outcomes.
New method identifies proxies for causal effects on multiple outcomes.
Study uses surrogate data to improve treatment effect estimation with scarce outcome data.
The paper targets optimal interventions for long-term outcomes using imputed data and policy learning.
Bayesian optimization learns DM preferences for multi-outcome experiments.
There is tremendous interest in precision medicine as a means to improve patient outcomes by tailoring treatment to individual characteristics. An individualized treatment rule formalizes precision medicine as a map from patient information to a recommended treatment. A treatment rule is defined to be optimal if it max…
Discusses handling intercurrent events in clinical trials with time-to-event outcomes.
We study notions of fairness in decision-making systems when individuals have diverse preferences over the possible outcomes of the decisions. Our starting point is the seminal work of Dwork et al. which introduced a notion of individual fairness (IF): given a task-specific similarity metric, every pair of individuals …
Flow IV uses IVs to infer counterfactuals in complex models.
Study uses remotely sensed data to infer economic outcomes in experiments and quasi-experiments.