## Ionic Sieving Through One Atom Thick 2D Material Enables Analog Nonvolatile Memory for Neuromorphic Computing

The first report on ion transport through atomic sieves of atomically-thin 2Dmaterial is provided to solve critical limitations of electrochemicalrandom-access memory (ECRAM) devices .…

## Blazing a Trail via Matrix Multiplications A Faster Algorithm for Non shortest Induced Paths

For vertices $u$ and $v$ of an $n$-vertex graph, a $uv$-trail of $G$ is an induced path of $U$ that is not a shortest $uv$. path . We reduce complexity to the time required to perform a poly-logarithmic number of multiplications of $n^2\times n^2$ Booleanmatrices .…

## Deep Contextual Video Compression

Most of the existing neural video compression methods adopt the predictivecoding framework, which first generates the predicted frame and then encodesits residue with the current frame . To tap the potential of conditional coding, we proposeusing feature domain context as condition .…

## Reinforcement Learning with Information Theoretic Actuation

Reinforcement Learning formalises an embodied agent’s interaction with the environment through observations, rewards and actions . But where do the actions come from? Actions are often considered to represent something external, such as the movement of a limb, a chess piece, or more generally, the output of an action model .…

## preCICE v2 A Sustainable and User Friendly Coupling Library

preCICE is a free/open-source coupling library . It enables creatingpartitioned multi-physics simulations by gluing together separate software packages . We cover the fundamentals of the software alongside aperformance and accuracy analysis of different data mapping methods . Afterwards, we describe ready-to-use integration with widely-used externalsimulation software packages, tests and continuous integration from unit tosystem level, and community building measures, drawing an overview of thepreCICE ecosystem .…

## Variational learning of quantum ground states on spiking neuromorphic hardware

We train a neuromorphic hardware chip to approximate the ground states of quantum spin models by variational energy minimization . We develop atraining algorithm and apply it to the transverse field Ising model, showing good performance at moderate system sizes .…

## Process discovery on deviant traces and other stranger things

Process discovery research field has gained more importance, developing two different classes of approaches to modelrepresentation . We focus on declarative processes and embrace the less-popular view of process discovery as a binary supervisedlearning task . We therefore deepen how valuable information brought by both sets can be extracted and formalised into a model that is”optimal” according to user-defined goals .…

## Rectangular Spiral Galaxies are Still Hard

Spiral Galaxies is a pencil-and-paper puzzle played on a grid of unitsquares . The goal is to partition the grid into polyominoes such that each center contains exactly one center and is rotationally symmetric about its center . We prove NP-completeness of the designproblem of minimizing the number of centers such that there exist a set ofSpiral Galaxies that exactly cover a given shape .…

## Benchmarking a Probabilistic Coprocessor

Computation in the past decades has been driven by deterministic computers based on classical deterministic bits . Recently, alternative computing paradigms like quantum computing and probabilistic computing have gained traction . To efficiently implement Monte Carlo algorithms the generation of random numbers is crucial .…

## Approximating the Bundled Crossing Number

There is a polynomial time algorithm to compute an 8-approximation of the bundled crossing number of a good drawing (upto adding a term depending on the facial structure of the drawing) In the special case of circular drawings the approximation factor is 8 (no extraterm), this improves upon the 10-approxyimation of Fink et al.…

## Modeling Interactions of Autonomous Vehicles and Pedestrians with Deep Multi Agent Reinforcement Learning for Collision Avoidance

The sequential nature of thevehicle-pedestrian interaction is an often neglected but important aspect of the interaction . We model the corresponding interaction sequence as a Markov decision process (MDP) that is solved by deepreinforcement learning (DRL) algorithms . The results show that the AV is able to mitigate collisions under the majority of the investigated conditions and that the DRL-based pedestrian model indeed learns a more human-like crossing behavior .…

## A first moment proof of the Johansson Molloy theorem

We give a short proof of a stronger form of the Johansson-Molloy theorem . The proof adapts a clever counting argument developed by Rosenfeld in the context of non-repetitive colourings . We then extend that result to graphswhere each neighbourhood has bounded density .…

## A Fibonacci type sequence with Prouhet Thue Morse coefficients

The sequence is the well-known Prouhet-Thue-Morse sequence . We prove several arithmetic properties concerning arithmetic properties of the sequence . In particular, we prove non-vanishing of $h_n$ for $n \ge 5$ and automaticityof the sequence $n\in \mathbb N}$ for each m, and other results .…

## A formal model for ledger management systems based on contracts and temporal logic

A key component of blockchain technology is the ledger, viz., a databasethat, unlike standard databases, keeps in memory the complete history of past transactions . In second-generation blockchains the ledger is coupled with smartcontracts, which enable the automation of transactions associated with agreements between parties of a financial or commercial nature .…

## Approximating the Bundled Crossing Number

There is a polynomial time algorithm to compute an 8-approximation of the bundled crossing number of a good drawing (upto adding a term depending on the facial structure of the drawing) In the special case of circular drawings the approximation factor is 8 (no extraterm), this improves upon the 10-approxyimation of Fink et al.…

## Rectangular Spiral Galaxies are Still Hard

Spiral Galaxies is a pencil-and-paper puzzle played on a grid of unitsquares . The goal is to partition the grid into polyominoes such that each center contains exactly one center and is rotationally symmetric about its center . We prove NP-completeness of the designproblem of minimizing the number of centers such that there exist a set ofSpiral Galaxies that exactly cover a given shape .…

## Unified Shader Programming in C

In real-time graphics, the strict separation of programming languages and environments for host (CPU) code and GPU code results in code duplication, compatibility bugs, and additional development and maintenance costs . Popular general-purpose GPU (GPGPU) programming models like CUDA andC++ AMP avoid many of these issues by presenting unified programming environments .…

## Combining Sobolev Smoothing with Parameterized Shape Optimization

Sobolev gradient smoothing can considerably improve the performance of aerodynamic shape optimization and prevent issues with regularity . The incorporation of the parameterizationallows for direct application to engineering test cases, where shapes are described by a CAD model . The new methodology presented in this paper is used for reference test cases from aerodynamics shape optimization, and performance improvements in comparison to a classical Quasi-Newton scheme are shown .…

## Deciding All Behavioral Equivalences at Once A Game for Linear time Branching time Spectroscopy

We introduce a generalization of the bisimulation game that can be employed to find all relevant distinguishing Hennessy–Milner logic formulas for twocompared finite-state processes . The induced algorithm can determine the best fit of (in)equivalences for a pair of processes .…

## Width Based Planning and Active Learning for Atari

Width-based planning has shown promising results on Atari 2600 games usingpixel input . Recent width-based approaches have computed featurevectors for each screen using a hand designed feature set or a variationalautoencoder (VAE) trained on game screens . In this paper, we explore consideration ofuncertainty in features generated by a VAE during planning .…

## Learning to Superoptimize Real world Programs

SelfImitation Learning for Optimization (SILO) superoptimizes programs an expected 6.2% of our test set . SILO’s rate of superoptimization onour test set is over five times that of a standard policy gradient approach and a model pre-trained on compiler optimization demonstration.…

## A Spatial Agent Based Model for Preemptive Evacuation Decisions During Typhoon

The Philippines, due to its geographic location, is considered anatural disaster-prone country experiencing an average of 20 tropical cyclones annually . Understanding what factors significantly affect decision making could help in making decisions on how toprepare for disasters, how to act appropriately and strategically respondduring and after a calamity .…

## Conceptual Data Modeling Entity Relationship Models as Thinging Machines

Data modeling is a process of developing a model to design and develop a datasystem that supports an organization s various business processes . A conceptualdata model represents a technology-independent specification of structure of data to be stored in a database .…

## An FE DMN method for the multiscale analysis of thermodynamical composites

Every Gauss point of themacroscopic finite element model is equipped with a deep material network(DMN) Such a DMN serves as a high-fidelity surrogate model for full-fieldsolutions on the microscopic scale of inelastic, non-isothermal constituents . We extend the FE-DMN method to fully coupled thermomechanical two-scalesimulations of composite materials .…

## Neural Knitworks Patched Neural Implicit Representation Networks

Coordinate-based Multilayer Perceptron (MLP) networks are not performant for internal image synthesis applications . Convolutional Neural Networks (CNNs) are typically used instead for a variety of internal generative tasks, at the cost of a larger model . We propose Neural Knitwork, an architecture for neuralimplicit representation learning of natural images that achieves imagesynthesis by optimizing the distribution of image patches in an adversarialmanner .…

## n Qubit Operations on Sphere and Queueing Scaling Limits for Programmable Quantum Computer

We study n-qubit operation rules on (n+1)-sphere with the target to helpdeveloping a (photon or other technique) based programmable quantum computer . In the first regime, the qubit number $n$ isfixed and the scaling is in terms of both time and space .…

## Unified Shader Programming in C

In real-time graphics, the strict separation of programming languages and environments for host (CPU) code and GPU code results in code duplication, compatibility bugs, and additional development and maintenance costs . Popular general-purpose GPU (GPGPU) programming models like CUDA andC++ AMP avoid many of these issues by presenting unified programming environments .…

## Stock Index Prediction using Cointegration test and Quantile Loss

Recent researches on stock prediction using deep learning methods has been studied . This is the task to predict the movement of stock prices inthe future based on historical trends . The approach to predicting the movementbased solely on the pattern of the historical movement of it on charts, not onfundamental values, is called the Technical Analysis .…

## Visualization Design Sprints for Online and On Campus Courses

A design sprint is a unique process based on rapid prototyping and user testing to define goals and validate ideas before costly development . The well-defined, interactive, and time-constrained design cycle makes design sprints a promising option for teaching project-based and active-learning-centered courses to increase studentengagement and hands-on experience .…

## Identity Expression Ambiguity in 3D Morphable Face Models

3D Morphable Models are a class of generative models commonly used to modelfaces . They are typically applied to ill-posed problems such as 3Dreconstruction from 2D data . We demonstrate that non-orthogonality of the variation in variation in identity and expression can causeidentity-expression ambiguity in 3Dmorphable Models .…

## An epistemic approach to model uncertainty in data graphs

Graph databases are becoming widely successful as data models that allow to represent and process complex relationships among various types of data . As with any other type of data repository, graph databases may suffer from errors and discrepancies with respect to the real-world data they intend to represent .…

## Gaps Ambiguity and Establishing Complexity Class Containments via Iterative Constant Setting

Cai and Hemachandra used iterative constant-setting to prove that Few$\subseteq$ $\oplus$P (and thus that FewP \$1) is a restricted counting class . Their work lowers the bar for what advances regarding the existence of infinite, P-printable sets of primes would suffice to show that restricted counting classes based on the primes have the power to accept superconstant-ambiguity analogues of UP .…

## The Neural MMO Platform for Massively Multiagent Research

Neural MMO is a computationally accessible research platform that combines large agent populations, long time horizons, open-ended tasks, and modular gamesystems . We present Neural MMO as free and opensource software with active support, ongoing development, documentation, and training, logging, and visualization tools to help users adapt to the new setting .…