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.
Study re-evaluates MIMIC-III codes, finding many are under-coded.
Robust machine learning relies on access to data that can be used with standardized frameworks in important tasks and the ability to develop models whose performance can be reasonably reproduced. In machine learning for healthcare, the community faces reproducibility challenges due to a lack of publicly accessible data…
Paper proposes sharing models instead of data for smart health predictions.
Scoping review and benchmarking of synthetic EHR data generation methods.
We consider technology-assisted mimicry attacks in the context of automatic speaker verification (ASV). We use ASV itself to select targeted speakers to be attacked by human-based mimicry. We recorded 6 naive mimics for whom we select target celebrities from VoxCeleb1 and VoxCeleb2 corpora (7,365 potential targets) usi…
GRU-D detects age-specific missing patterns in vital signs.
Relational Mimic improves visual imitation learning from video demonstrations.
Purveyors of malicious network attacks continue to increase the complexity and the sophistication of their techniques, and their ability to evade detection continues to improve as well. Hence, intrusion detection systems must also evolve to meet these increasingly challenging threats. Machine learning is often used to …
Deep Reinforcement Learning (DRL) has achieved impressive success in many applications. A key component of many DRL models is a neural network representing a Q function, to estimate the expected cumulative reward following a state-action pair. The Q function neural network contains a lot of implicit knowledge about the…
Given independent samples generated from the joint distribution , we study the problem of Conditional Independence (CI-Testing), i.e., whether the joint equals the CI distribution $p^{CI}(\mathbf{x},\mathbf{y},\mathbf{z})= p(\mathbf{z}) p(\mathbf{y}|\mathbf{z})p(\mathbf{x}|\mathbf{z…
Framework improves clinical timeline reconstruction from text and tables.
Model predicts patient outcomes from EHR data by limiting feature interactions.
Study evaluates federated learning with differential privacy on MIMIC-III, improving model performance with careful parameter tuning.
We present a method to develop a Hodge theory for tangential cohomology of foliations by mimicing Witten's approach to ordinary Morse theory by perturbations of the Laplacian
FMI uses matching to mimic interventions for causal feature learning.
We construct a canonically defined affine connection in sub-Riemannian contact geometry. Our method mimics that of the Levi-Civita connection in Riemannian geometry. We compare it with the Tanaka-Webster connection in the three-dimensional case.
Study develops an interpretable model for early mortality prediction in elderly MODS patients.
New model mimics neural next item recommendation using Hankel matrices.
Yes, they do. This paper provides the first empirical demonstration that deep convolutional models really need to be both deep and convolutional, even when trained with methods such as distillation that allow small or shallow models of high accuracy to be trained. Although previous research showed that shallow feed-for…
Two different spacetimes can mimic each other's boundary measurements.
Simulates sepsis treatment decisions using a world model approach.
New method steals deep neural network knowledge using unlabeled data.
PIN models feature interactions using a neural network that mimics decision trees.
Probabilistic survival predictions from models trained with Maximum Likelihood Estimation (MLE) can have high, and sometimes unacceptably high variance. The field of meteorology, where the paradigm of maximizing sharpness subject to calibration is popular, has addressed this problem by using scoring rules beyond MLE, s…
The paper develops a faster surrogate model for simulators using hybrid methods.
Paper simplifies complex sports analytics models for better understanding.
The paper tackles ICU discharge strategies by evaluating optimal stopping scenarios.
Neural networks mimic algorithms to solve complex problems.
Improves medical note processing by training model on related concepts and global context.
Machine learning for healthcare often trains models on de-identified datasets with randomly-shifted calendar dates, ignoring the fact that data were generated under hospital operation practices that change over time. These changing practices induce definitive changes in observed data which confound evaluations which do…
There has been significant recent interest towards achieving highly efficient deep neural network architectures. A promising paradigm for achieving this is the concept of evolutionary deep intelligence, which attempts to mimic biological evolution processes to synthesize highly-efficient deep neural networks over succe…
Imitation Learning is a sequential task where the learner tries to mimic an expert's action in order to achieve the best performance. Several algorithms have been proposed recently for this task. In this project, we aim at proposing a wide review of these algorithms, presenting their main features and comparing them on…
Study benchmarks uncertainty quantification in chest X-ray classification.
Automated medical prognosis has gained interest as artificial intelligence evolves and the potential for computer-aided medicine becomes evident. Nevertheless, it is challenging to design an effective system that, given a patient's medical history, is able to predict probable future conditions. Previous works, mostly c…
Deep learning models (aka Deep Neural Networks) have revolutionized many fields including computer vision, natural language processing, speech recognition, and is being increasingly used in clinical healthcare applications. However, few works exist which have benchmarked the performance of the deep learning models with…
Deep learning predicts ICU mortality with enhanced interpretability.
We prove that every Teichmuller geodesic of a finite type surface contains a string of intersecting long, thick and dominant segments, such that the distance between consecutive segments is bounded. This is key to obtaining some results about Teichmuller geodesics which mimic those for hyperbolic geodesics. These resul…
We study multiple rule-based and machine learning (ML) models for sepsis detection. We report the first neural network detection and prediction results on three categories of sepsis. We have used the retrospective Medical Information Mart for Intensive Care (MIMIC)-III dataset, restricted to intensive care unit (ICU) p…
MedCAT extracts valuable medical information from unstructured text.
New formula for spherical polygon area via prequantization.
Improved aggregation methods learn from all ICU events without preprocessing for better patient risk analysis.
New method improves compatibility of risk stratification models without sacrificing accuracy.
Cubic spline interpolation on Euclidean space is a standard topic in numerical analysis, with countless applications in science and technology. In several emerging fields, for example computer vision and quantum control, there is a growing need for spline interpolation on curved, non-Euclidean space. The generalization…
LLMs mimic human traders in finance, but not as much as expected.
This paper uses Gaussian mixtures to mimic interactions in large language models.
How do individuals accumulate wealth as they interact economically? We outline the consequences of a simple microscopic model in which repeated pairwise exchanges of assets between individuals build the wealth distribution of a population. This distribution is determined for generic exchange rules --- transactions that…
Three physics-constrained regression exercises for image velocimetry and turbulence modeling.
X-CAL improves survival model calibration without sacrificing predictive power.