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Optical flow estimation is one of the most studied problems in computer vision, yet recent benchmark datasets continue to reveal problem areas of today's approaches. Occlusions have remained one of the key challenges. In this paper, we…

Computer Vision and Pattern Recognition · Computer Science 2017-08-18 Junhwa Hur , Stefan Roth

This article is about twofold arithmetic. Here I introduce algorithms and experimental code for twofold variant of C/C++ standard functions exp() and log(), and expm1() and log1p(). Twofold function $y_0+y_1 \approx f(x_0+x_1)$ is nearly…

Mathematical Software · Computer Science 2015-02-19 Evgeny Latkin

Floating-point arithmetic plays a central role in science, engineering, and finance by enabling developers to approximate real arithmetic. To address numerical issues in large floating-point applications, developers must identify root…

Programming Languages · Computer Science 2018-07-02 Alex Sanchez-Stern , Pavel Panchekha , Sorin Lerner , Zachary Tatlock

Recent research has demonstrated that quantum computers can solve certain types of problems substantially faster than the known classical algorithms. These problems include factoring integers and certain physics simulations. Practical…

Quantum Physics · Physics 2009-10-30 Emanuel Knill , Raymond Laflamme , Wojciech H. Zurek

High-rate and large-distance quantum codes are expected to make fault-tolerant quantum computing more efficient, but most of them lack efficient fault-tolerant encoded-state preparation methods. We propose such a fault-tolerant encoder for…

Quantum Physics · Physics 2025-09-22 Naoyuki Kanomata , Hayato Goto

Numerical simulations of merging compact objects and their remnants form the theoretical foundation for gravitational wave and multi-messenger astronomy. While Cartesian-coordinate-based adaptive mesh refinement is commonly used for…

Large language models (LLMs), with their billions of parameters, pose substantial challenges for deployment on edge devices, straining both memory capacity and computational resources. Block Floating Point (BFP) quantisation reduces memory…

Hardware Architecture · Computer Science 2025-04-23 Xiaomeng Han , Yuan Cheng , Jing Wang , Junyang Lu , Hui Wang , X. x. Zhang , Ning Xu , Dawei Yang , Zhe Jiang

Dual numbers are a well-established tool for computing derivatives and constitute the basis of forward-mode automatic differentiation. While the theoretical framework for computing derivatives of arbitrary order is well understood,…

Numerical Analysis · Mathematics 2026-02-06 F. Peñuñuri , K. B. Cantún-Avila , R. Peón-Escalante

We consider the computation of the matrix logarithm by using numerical quadrature. The efficiency of numerical quadrature depends on the integrand and the choice of quadrature formula. The Gauss--Legendre quadrature has been conventionally…

Numerical Analysis · Mathematics 2019-09-09 Fuminori Tatsuoka , Tomohiro Sogabe , Yuto Miyatake , Shao-Liang Zhang

We provide a correction to the sufficient conditions under which closed-form expressions for the optimal Lagrange multiplier are provided in arXiv:2112.13138 [math.OC]. We first present a simple counterexample where the original conditions…

Optimization and Control · Mathematics 2025-03-13 Henri Lefebvre , Anirudh Subramanyam

Proper representation of data in graphical visualizations becomes challenging when high accuracy in data types is required, especially in those situations where the difference between double-precision floating-point and single-precision…

Graphics · Computer Science 2024-08-20 Nezihe Sozen

Our goal is to find accurate and efficient algorithms, when they exist, for evaluating rational expressions containing floating point numbers, and for computing matrix factorizations (like LU and the SVD) of matrices with rational…

Numerical Analysis · Mathematics 2025-10-20 James Demmel

Real-world time series analysis faces significant challenges when dealing with irregular and incomplete data. While Neural Differential Equation (NDE) based methods have shown promise, they struggle with limited expressiveness, scalability…

Machine Learning · Computer Science 2026-04-03 YongKyung Oh , Dong-Young Lim , Sungil Kim

Two optical flow estimation problems are addressed: i) occlusion estimation and handling, and ii) estimation from image sequences longer than two frames. The proposed ContinualFlow method estimates occlusions before flow, avoiding the use…

Computer Vision and Pattern Recognition · Computer Science 2018-11-06 Michal Neoral , Jan Šochman , Jiří Matas

Data association in SLAM is fundamentally challenging, and handling ambiguity well is crucial to achieve robust operation in real-world environments. When ambiguous measurements arise, conservatism often mandates that the measurement is…

Robotics · Computer Science 2019-03-07 Kristoffer M. Frey , Ted J. Steiner , Jonathan P. How

Significant inaccuracy often occurs during the process of mathematical calculation due to the digit limitation of floating point, which may lead to catastrophic loss. Normally, people believe that adjustment of floating-point precision is…

Numerical Analysis · Computer Science 2015-12-07 Ran Wang , Xinrui He

We introduce MathConstraint, a hard, adaptive benchmark for evaluating the combinatorial reasoning capabilities of LLMs. We combine constraint satisfaction problems with rigorous solver-based verification and design an adaptive generator to…

Machine Learning · Computer Science 2026-05-12 Viresh Pati , Zhengyu Li , Piyush Jha , Rahul Garg , Yatharth Sejpal , Vijay Ganesh

As computer simulations continue to grow in size and complexity, they present a particularly challenging class of big data problems. Many application areas are moving toward exascale computing systems, systems that perform $10^{18}$ FLOPS…

The occlusion problem remains a crucial challenge in optical flow estimation (OFE). Despite the recent significant progress brought about by deep learning, most existing deep learning OFE methods still struggle to handle occlusions; in…

Computer Vision and Pattern Recognition · Computer Science 2024-03-05 Bo Wang , Yifan Zhang , Jian Li , Yang Yu , Zhenping Sun , Li Liu , Dewen Hu

We introduce primal and dual stochastic gradient oracle methods for decentralized convex optimization problems. Both for primal and dual oracles, the proposed methods are optimal in terms of the number of communication steps. However, for…

Optimization and Control · Mathematics 2021-02-12 Darina Dvinskikh , Alexander Gasnikov
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