Papers Unity
“Unity” 태그가 달린 논문 378편 · 필터 해제
Testing for Coefficient Randomness in Local-to-Unity Autoregressions
In this study, we propose a test for the coefficient randomness in autoregressive models where the autoregressive coefficient is local to unity, which is empirically relevant given the results of earlier studies. Under t…
UnityOn the functional form of the radial acceleration relation
We apply a new method for learning equations from data -- Exhaustive Symbolic Regression (ESR) -- to late-type galaxy dynamics as encapsulated in the radial acceleration relation (RAR). Relating the centripetal accelerat…
FormregressionRelationSymbolic Regression+1VQNet 2.0: A New Generation Machine Learning Framework that Unifies Classical and Quantum
With the rapid development of classical and quantum machine learning, a large number of machine learning frameworks have been proposed. However, existing machine learning frameworks usually only focus on classical or qua…
Quantum Machine LearningUnityRethinking Mobile Block for Efficient Attention-based Models
This paper focuses on developing modern, efficient, lightweight models for dense predictions while trading off parameters, FLOPs, and performance. Inverted Residual Block (IRB) serves as the infrastructure for lightweigh…
UnityIthaca. A Tool for Integrating Fuzzy Logic in Unity
Ithaca is a Fuzzy Logic (FL) plugin for developing artificial intelligence systems within the Unity game engine. Its goal is to provide an intuitive and natural way to build advanced artificial intelligence systems, maki…
UnitySituation-Aware Deep Reinforcement Learning for Autonomous Nonlinear Mobility Control in Cyber-Physical Loitering Munition Systems
According to the rapid development of drone technologies, drones are widely used in many applications including military domains. In this paper, a novel situation-aware DRL- based autonomous nonlinear drone mobility cont…
Deep Reinforcement LearningUnityIdentifying causal effects with subjective ordinal outcomes
Survey questions often ask respondents to select from ordered scales where the meanings of the categories are subjective, leaving each individual free to apply their own definitions in answering. This paper studies the u…
Causal IdentificationCausal InferenceregressionUnityTask-Guided IRL in POMDPs that Scales
In inverse reinforcement learning (IRL), a learning agent infers a reward function encoding the underlying task using demonstrations from experts. However, many existing IRL techniques make the often unrealistic assumpti…
UnityExample-guided learning of stochastic human driving policies using deep reinforcement learning
Deep reinforcement learning has been successfully applied to the generation of goal-directed behavior in artificial agents. However, existing algorithms are often not designed to reproduce human-like behavior, which may …
Autonomous VehiclesDeep Reinforcement LearningGaussian Processesreinforcement-learning+3UnitY: Two-pass Direct Speech-to-speech Translation with Discrete Units
Direct speech-to-speech translation (S2ST), in which all components can be optimized jointly, is advantageous over cascaded approaches to achieve fast inference with a simplified pipeline. We present a novel two-pass dir…
DecoderDenoisingSpeech-to-Speech TranslationTranslation+2A Novel Approach For Generating Customizable Light Field Datasets for Machine Learning
To train deep learning models, which often outperform traditional approaches, large datasets of a specified medium, e.g., images, are used in numerous areas. However, for light field-specific machine learning tasks, ther…
Deep LearningUnityCAD2Render: A Modular Toolkit for GPU-accelerated Photorealistic Synthetic Data Generation for the Manufacturing Industry
The use of computer vision for product and assembly quality control is becoming ubiquitous in the manufacturing industry. Lately, it is apparent that machine learning based solutions are outperforming classical computer …
GPUobject-detectionObject DetectionPose Estimation+2Pac-Man Pete: An extensible framework for building AI in VEX Robotics
This technical report details VEX Robotics team BLRSAI's development of a fully autonomous robot for VEX Robotics' Tipping Point AI Competition. We identify and develop three separate critical components. This includes a…
reinforcement-learningReinforcement Learning (RL)UnityOptimal Design of Volt/VAR Control Rules of Inverters using Deep Learning
Distribution grids are challenged by rapid voltage fluctuations induced by variable power injections from distributed energy resources (DERs). To regulate voltage, the IEEE Standard 1547 recommends each DER inject reacti…
BenchmarkingUnityLearning Visualization Policies of Augmented Reality for Human-Robot Collaboration
In human-robot collaboration domains, augmented reality (AR) technologies have enabled people to visualize the state of robots. Current AR-based visualization policies are designed manually, which requires a lot of human…
UnityDART: Articulated Hand Model with Diverse Accessories and Rich Textures
Hand, the bearer of human productivity and intelligence, is receiving much attention due to the recent fever of digital twins. Among different hand morphable models, MANO has been widely used in vision and graphics commu…
DiversityHand Pose EstimationPose EstimationUnityMultiagent Reinforcement Learning Based on Fusion-Multiactor-Attention-Critic for Multiple-Unmanned-Aerial-Vehicle Navigation Control
The proliferation of unmanned aerial vehicles (UAVs) has spawned a variety of intelligent services, where efficient coordination plays a significant role in increasing the effectiveness of cooperative execution. However,…
Deep Reinforcement LearningMulti-agent Reinforcement Learningreinforcement-learningReinforcement Learning (RL)+2Propagation Stability Concepts for Network Synchronization Processes
A notion of disturbance propagation stability is defined for dynamical network processes, in terms of decrescence of an input-output energy metric along cutsets away from the disturbance source. A characterization of the…
UnityProbabilistic partition of unity networks for high-dimensional regression problems
We explore the probabilistic partition of unity network (PPOU-Net) model in the context of high-dimensional regression problems and propose a general framework focusing on adaptive dimensionality reduction. With the prop…
Dimensionality ReductionMixture-of-ExpertsregressionUnity+1The Local to Unity Dynamic Tobit Model
This paper considers highly persistent time series that are subject to nonlinearities in the form of censoring or an occasionally binding constraint, such as are regularly encountered in macroeconomics. A tractable candi…
modelTime SeriesTime Series AnalysisUnity