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In domains with interdependent data, such as graphs, quantifying the epistemic uncertainty of a Graph Neural Network (GNN) is challenging as uncertainty can arise at different structural scales. Existing techniques neglect this issue or…

Machine Learning · Computer Science 2025-02-28 Dominik Fuchsgruber , Tom Wollschläger , Stephan Günnemann

For an $n$-vertex graph $G$, let $z(G;k)$ denote the number of zero forcing sets of size $k$. A conjecture of Boyer et al. asserts that the path $P_n$ maximizes these numbers coefficientwise among all $n$-vertex graphs; equivalently, the…

Discrete Mathematics · Computer Science 2026-05-12 Samuel German

Energy-based models (EBMs) are powerful probabilistic models, but suffer from intractable sampling and density evaluation due to the partition function. As a result, inference in EBMs relies on approximate sampling algorithms, leading to a…

Machine Learning · Computer Science 2020-01-10 Dieterich Lawson , George Tucker , Bo Dai , Rajesh Ranganath

Weighted ensemble (WE) is an enhanced path-sampling method that is conceptually simple, widely applicable, and statistically exact. In a WE simulation, an ensemble of trajectories is periodically pruned or replicated to enhance sampling of…

We study the joint scheduling of behind-the-meter distributed energy resources (DERs), including flexible loads, renewable generation, and battery energy storage systems, under net energy metering tariffs with demand charges. The problem is…

Systems and Control · Electrical Eng. & Systems 2026-01-07 Ruixiao Yang , Gulai Shen , Ahmed S. Alahmed , Chuchu Fan

Makespan minimization in restricted assignment $(R|p_{ij}\in \{p_j, \infty\}|C_{\max})$ is a classical problem in the field of machine scheduling. In a landmark paper in 1990 [8], Lenstra, Shmoys, and Tardos gave a 2-approximation algorithm…

Data Structures and Algorithms · Computer Science 2015-10-05 Chien-Chung Huang , Sebastian Ott

Maximum likelihood estimation of energy-based models is a challenging problem due to the intractability of the log-likelihood gradient. In this work, we propose learning both the energy function and an amortized approximate sampling…

Machine Learning · Computer Science 2019-05-29 Rithesh Kumar , Sherjil Ozair , Anirudh Goyal , Aaron Courville , Yoshua Bengio

The diameter, radius and eccentricities are natural graph parameters. While these problems have been studied extensively, there are no known dynamic algorithms for them beyond the ones that follow from trivial recomputation after each…

Data Structures and Algorithms · Computer Science 2019-12-18 Bertie Ancona , Monika Henzinger , Liam Roditty , Virginia Vassilevska Williams , Nicole Wein

An edge-weighted graph $G=(V,E)$ is called stable if the value of a maximum-weight matching equals the value of a maximum-weight fractional matching. Stable graphs play an important role in some interesting game theory problems, such as…

Data Structures and Algorithms · Computer Science 2017-11-28 Zhuan Khye Koh , Laura Sanità

A low-latency and energy-efficient tensor algebra accelerator design must optimize how data movement and operations are scheduled (i.e., mapped) in the accelerator architecture. A key mapping optimization is fusion, meaning holding data…

Hardware Architecture · Computer Science 2026-05-05 Tanner Andrulis , Michael Gilbert , Vivienne Sze , Joel S. Emer

In this paper, the probability distribution of the peak to average power ratio (PAPR) is analyzed for the mixed numerologies transmission based on orthogonal frequency division multiplexing (OFDM). State of the art theoretical analysis…

Signal Processing · Electrical Eng. & Systems 2019-11-26 Xiaoran Liu , Lei Zhang , Jun Xiong , Xiaoying Zhang , Li Zhou , Jibo Wei

Artificial intelligence can rapidly propose candidate phases and structures from X-ray diffraction (XRD), but these hypotheses often fail in downstream refinement because peak intensities cannot be stably assigned under severe overlap and…

Materials Science · Physics 2026-02-25 Bin Cao , Qian Zhang , Zhenjie Feng , Taolue Zhang , Jiaqiang Huang , Lu-Tao Weng , Tong-Yi Zhang

In comparison with the accurate data on the on-top electron density n(0) in the proton-embedded electron gas with the density parameter r_s in the range 1-12 obtained by diffusion Monte Carlo (DMC) simulations, we have successfully…

Materials Science · Physics 2018-07-18 Yasutami Takada

We investigate two notions of saturation for partial planar embeddings of maximal planar graphs. Let $G = (V, E) $ be a vertex-labeled maximal planar graph on $ n $ vertices, which by definition has $3n - 6$ edges. We say that a labeled…

Combinatorics · Mathematics 2024-12-10 Alexander Clifton , Dániel G. Simon

Let $G$ be a graph on $n$ vertices with independence number $\alpha(G)$. Let $\mathcal{E}(G)$ be the energy of a graph, defined as the sum of the absolute values of the adjacency eigenvalues of $G$. Using Graffiti, Fajtlowicz conjectured in…

Combinatorics · Mathematics 2025-09-09 Aida Abiad , Gabriel Coutinho , Emanuel Juliano , Luuk Reijnders

Power systems face increasing challenges in maintaining resource adequacy due to lower operating margins, rising renewable energy uncertainty, and demand variability. Forecasting the probability distribution of peak demand on shorter…

Systems and Control · Electrical Eng. & Systems 2025-10-28 Buyi Yu , Wenyuan Tang

The alignment strength of a graph matching is a quantity that gives the practitioner a measure of the correlation of the two graphs, and it can also give the practitioner a sense for whether the graph matching algorithm found the true…

Wattenhofer [WW04] derive a complicated distributed algorithm to compute a weighted matching of an arbitrary weighted graph, that is at most a factor 5 away from the maximum weighted matching of that graph. We show that a variant of the…

Distributed, Parallel, and Cluster Computing · Computer Science 2007-05-23 Jaap-Henk Hoepman

A novel embedded atom method (EAM) potential for the Xi-phases of Al-Pd-Mn has been determined with the force-matching method. Different combinations of analytic functions were tested for the pair and transfer part. The best results are…

Materials Science · Physics 2012-02-09 Daniel Schopf , Peter Brommer , Benjamin Frigan , Hans-Rainer Trebin

Splitting schemes are a class of powerful algorithms that solve complicated monotone inclusions and convex optimization problems that are built from many simpler pieces. They give rise to algorithms in which the simple pieces of the…

Optimization and Control · Mathematics 2015-05-19 Damek Davis , Wotao Yin
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