Intensional Artificial Intelligence From Symbol Emergence to Explainable and Empathetic AI

We argue that an explainable artificial intelligence must possess a rationalefor its decisions, be able to infer the purpose of observed behaviour . To communicate that rationale requires naturallanguage, a means of encoding and decoding perceptual states . We propose atheory of meaning in which, to acquire language, an agent should model the world a language describes rather than the language itself.…

Understanding who uses Reddit Profiling individuals with a self reported bipolar disorder diagnosis

This paper shows how existing NLP methods can yield information on clinical, demographic, and identity characteristics of almost 20K Reddit users who self-report a bipolar disorder diagnosis . This population consists ofslightly more feminine- than masculine-gendered mainly young or middle-aged US-based adults who often report additional mental health diagnoses, which iscompared with general Reddit statistics and epidemiological studies .…

Discrete Maximum principle of a high order finite difference scheme for a generalized Allen Cahn equation

We consider solving a generalized Allen-Cahn equation coupled with a passive convection for a given incompressible velocity field . We prove that the discrete maximum principle holds under suitable meshsize and time step constraints . The same result also applies to construct abound-preserving scheme for any convection with an incompressablevelocity field, we say .…

Reduced order models for Lagrangian hydrodynamics

Lagrangian hydrodynamics is characterized by moving meshes, advection-dominated solutions, and moving shock fronts withsharp gradients . These challenges hinder the existing projection-based modelreduction schemes from being practical . Over-sampling DEIM and SNS approaches reduce complexity due to the nonlinear terms .…

Convexification based globally convergent numerical method for a 1D coefficient inverse problem with experimental data

To solve the inverse problem, we establish a new version of Carlemanestimate and then employ this estimate to construct a cost functional which isstrictly convex on a convex bounded set with an arbitrary diameter in a Hilbertspace . Minimizing this convex functional by the gradient descent method, we obtain the desired numerical solution to the coefficient inverse problems .…

Cross Domain and Disentangled Face Manipulation with 3D Guidance

Face image manipulation via three-dimensional guidance has been widelyapplied in various interactive scenarios due to its semantically-meaningfulunderstanding and user-friendly controllability . Existing 3D-morphable-model-based manipulation methods are not directly applicable toout-of-domain faces, such as non-photorealistic paintings, cartoon portraits, or even animals .…

Sketch based Normal Map Generation with Geometric Sampling

A designer may benefit from auto-generation of high quality and accurate maps from freehand sketches in 3D content creation . Normal map is an important and efficient way to represent complex 3D models . This paper proposes a deep generative model for generating normal maps from users sketch withgeometric sampling .…

Monitoring Cumulative Cost Properties

This paper considers the problem of decentralized monitoring of a class of non-functional properties (NFPs) with quantitative operators, namely cumulativecost properties . We address these issues by providing a formal framework fordecentralised monitoring of LTL formulas . The employment of these techniques allowsprocesses to detect early violations of monitored properties and perform somecorrective or recovery actions .…

Recording Reusable and Guided Analytics From Interaction Histories

We introduce avisual analysis tool that allows analysts to record reusable and guidedanalytics from their interaction logs . The tool enables analysts to formalize analysis strategies, build best practices, and guide novices through systematic workflows . It also enables users to use a decision tree whose node embeds visualizations and guide to define a visualanalysis task.…

iQUANT Interactive Quantitative Investment Using Sparse Regression Factors

The model-based investing using financial factors is evolving as a principalmethod for quantitative investment . The main challenge lies in the selection of effective factors towards excess market returns . This paper presents iQUANT, an interactive quantitative investment system that assists equitytraders to quickly spot promising financial factors from initialrecommendations suggested by algorithms .…

Learning in Deep Neural Networks Using a Biologically Inspired Optimizer

Plasticity circuits in the brain are known to be influenced by the distribution of the synaptic weights through the mechanisms of synaptic integration and local regulation of synaptic strength . Here, we propose a novel biologically inspired optimizer for artificial (ANNs) and spiking neural networks (SNNs) that incorporates keyprinciples of synapse integration observed in dendrites of cortical neurons:GRAPES .…

Literature review on vulnerability detection using NLP technology

Vulnerability detection has always been the most important task in the field of software security . In the face of massive source code, automated analysis and detection of vulnerabilities has become a current research hotspot . Using some of the hottest NLP technologies to build models and realize the automatic analysis of source code has become one of the mostanticipated studies .…

Uniformly accurate low regularity integrators for the Klein Gordon equation from the classical to non relativistic limit regime

We propose a novel class of uniformly accurate integrators for the Klein–Gordon equation . They capture classical $c=1$ as well as highly-oscillatory non-relativistic regimes $c\gg1$ and, at the same time,allow for low regularity approximations . The schemes converge under lower regularityassumptions than classical schemes, such as splitting or exponential integratormethods, require .…

A field guide to cultivating computational biology

Biomedical research centers can empower basic discovery and novel therapeutic strategies by leveraging their large-scale datasets from experiments and patients . This data, together with new technologies to create and analyze it, has ushered in an era of data-driven discovery which requires moving beyond thetraditional individual, single-discipline investigator research model .…

Active Learning of Sequential Transducers with Side Information about the Domain

Active learning is a setting in which a student queries a teacher, through membership and equivalence queries, in order to learn a language . In grayboxlearning, the learning process is accelerated by foreknowledge of someinformation on the target . We show that there exists an algorithm usingstring equation solvers that uses this knowledge to learn subsequential stringtransducers with a better guarantee on the required number of equivalencequeries than classical active learning .…

ESResNe X t fbsp Learning Robust Time Frequency Transformation of Audio

Environmental Sound Classification (ESC) is a rapidly evolving field that demonstrated advantages of application of visual domain techniquesto the audio-related tasks . We present a new time-frequency transformation layer that is based on complex frequency B-spline (fbsp) wavelets . The proposed fbsp-layer provides an accuracy improvement over the previously used Short-Time Fourier Transform (STFT) on standard datasets .…

Claim Detection in Biomedical Twitter Posts

Social media contains unfiltered and unique information, which is potentially of great value, but can also do great harm . Methods of automatic fact-checking and fake news detection addressthere problem, but have not been applied to the biomedical domain in socialmedia yet .…

Compilation based Solvers for Multi Agent Path Finding a Survey Discussion and Future Opportunities

Multi-agent path finding (MAPF) attracts considerable attention in artificialintelligence community . The task in the standard MAPF is to find paths throughwhich agents can navigate from their starting positions to specified individualgoal positions . The compilation-based MAPFsolving can benefit from advancements accumulated during the development of the target solver often decades long.…

Optimizing small BERTs trained for German NER

Currently, the most widespread neural network architecture for traininglanguage models is the so called BERT . In general, the larger the number of parameters in a BERT model, the results obtained in these NLP tasks . Unfortunately, the memory and training duration drastically increases with the size of these models .…

Algebraic combinatory models

We introduce an equationally definable counterpart of the notion ofcombinatory model . The new notion, called an algebraic combinatory model, is weaker than that of a Lambda algebra but is strong enough to interpret lambdacalculus . The resulting axiomatisation of Lambda algebras with the seven equations corresponds to that of Selinger [J.…

Graph Neural Network Reinforcement Learning for Autonomous Mobility on Demand Systems

Autonomous mobility-on-demand (AMoD) systems represent a rapidly developing mode of transportation . We propose a deep reinforcement learning framework to control the rebalancing of AMoD systems through graph neural networks . We show how the learned policies exhibit promising zero-shot transfer capabilities when faced with critical portability tasks such as inter-city generalization, service area expansion, and adaptation topotentially complex urban topologies.…

UAV Communications with WPT aided Cell Free Massive MIMO Systems

Cell-free (CF) massive multiple-input multiple- input multiple-output (MIMO) is a promisingsolution to provide uniform good performance for unmanned aerial vehicle (UAV) communications . The harvested energy from the downlink WPT is used to support both uplink data and pilottransmission . The maximum SE can be achieved by changing the time-splitting fraction of UAVs.…

Towards Automated Acceptance testing for industrial robots

Industrial robots are important machines applied in numerous modern industries that execute repetitive tasks with high accuracy . Automated AcceptanceTesting improves reliability for industrial robot program. We present theresearch question, the motivation for this study, our hypothesis and future research efforts.…

Model Checking for Verification of Quantum Circuits

Quantum assertions are specified by a temporal extension of Birkhoff-vonNeumann quantum logic . Algorithms for reachability analysis and model checking of quantum circuits are developed based on contraction of tensor networks . We observe that many optimisation techniques for computing relational products used inBDD-based model checking algorithms can be generalised for contracting tensornetworks of quantum circuit circuits .…

tcFFT Accelerating Half Precision FFT through Tensor Cores

Fast Fourier Transform (FFT) is an essential tool in scientific and engineering computation . The increasing demand for mixed-precision FFT has made it possible to utilize half-point (FP16) arithmetic forfaster speed and energy saving . Our tcFFT supports batched 1D and 2D FFT of various sizes and itexploits a set of optimizations to achieve high performance: 1) single-elementmanipulation on Tensor Core fragments to support special operations needed byFFT; 2) fine-grained data arrangement design to coordinate with the GPU memory access pattern .…

Speed Planning Using Bezier Polynomials with Trapezoidal Corridors

This paper studies speed planning, which mainly deals with dynamicobstacle avoidance given the planning path . The main challenges lie in the decisions in non-convex space and the trade-off between safety, comfort and efficiency performances . This work uses dynamic programming to search heuristicwaypoints on the S-T graph and to construct convex feasible spaces .…

OCRTOC A Cloud Based Competition and Benchmark for Robotic Grasping and Manipulation

The OCRTOC benchmark focuses on the objectrearrangement problem, specifically table organization tasks . We provide a set of identical real robot setups and facilitate remote experiments of standardized table organization scenarios in varying difficulties . We aim to lower the barrier of reproducible research on robotic grasping and manipulation andaccelerate progress in this field .…