arXiv research

Efficiently estimates SAGE values using causal structure learning.

Meta-SAGE improves deep RL scalability for CO tasks by adapting pre-trained models to larger-scale problems.

SAGE generates subsurface velocity models from sparse well logs and seismic images.

SAGE improves memory efficiency by selectively adding, merging, or ignoring new facts.

SAGE quantifies feature importance in machine learning models.

SAGE-FIN detects financial fraud using GNNs and Granger causality.

SAGE enhances reinforcement learning by injecting hints to prevent model stagnation.

Companies increasingly expose machine learning (ML) models trained over sensitive user data to untrusted domains, such as end-user devices and wide-access model stores. We present Sage, a differentially private (DP) ML platform that bounds the cumulative leakage of training data through models. Sage builds upon the ric…

A framework infers feature importance with uncertainties for high-dimensional data.

New method shows nonorientable surfaces in 4D are topologically unknotted.

New invariant identifies complex line arrangements with same combinatorics but different embeddings.

We provide elementary proofs of Lemmas 7.1 and 7.4 appearing in "The Cartan-Hadamard conjecture and the Little Prince", by B. Kloeckner and G. Kuperberg. The Lemmas play an important role in the derivation of novel isoperimetric inequalities. The original proofs relied on Sage, a symbolic algebra package, to factor cer…

We present a combinatorial proof for the existence of the sign refined grid homology in lens spaces, and a self contained proof that $\partial_{\mathbb{Z}}^2 = 0$. We also present a Sage program that computes $\widehat{\mathrm{GH}} (L(p,q),K;\mathbb{Z})$, and provide empirical evidence supporting the absence of torsion…

We provide a computer-assisted proof of the holomorphy of the quartic and the octic meromorphic differentials arising in the main Theorem 4.11 of our paper 'The Classification of Branched Willmore spheres in the $3$-Sphere and the $4$-Sphere' (arXiv:1706.01405), using the free mathematical software Sage.

GridPyM handles grid diagrams for knot theory.

GG-SAGE predicts links in directed graphs with attributes, outperforming existing methods.

In this work we simulate null geodesics for the Bonnor massive dipole metric by implementing a symbolic-numerical algorithm in Sage and Python. This program is also capable of visualizing in 3D, in principle, the geodesics for any given metric. Geodesics are launched from a common point, collectively forming a cone of …

Complete classification of Deligne-Mostow lattice representations into PGL(3,C).

SageMath package diffstrata calculates intersection theory on abelian differentials.

Shapley values criticized for feature selection, leading to new insights.

Graph Convolutional Networks (GCNs) have shown significant improvements in semi-supervised learning on graph-structured data. Concurrently, unsupervised learning of graph embeddings has benefited from the information contained in random walks. In this paper, we propose a model: Network of GCNs (N-GCN), which marries th…

We present an automatic classification method for astronomical catalogs with missing data. We use Bayesian networks, a probabilistic graphical model, that allows us to perform inference to pre- dict missing values given observed data and dependency relationships between variables. To learn a Bayesian network from incom…

Algorithm computes fundamental classes of spin components in moduli space.

BPt is a Python library for ML with neuroimaging data.

Machine learning improves Buchberger's algorithm for polynomial systems.

Solves Deligne-Simpson problem for special connections on Gm.

GNNs robustness in community detection is studied with various perturbations.

ENN method uses expectile regression for genetic data analysis of complex diseases.