Unity
77 papers with code • 0 benchmarks • 0 datasets
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Use these libraries to find Unity models and implementationsMost implemented papers
Pac-Man Pete: An extensible framework for building AI in VEX Robotics
blrsai/vexai-sim
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This technical report details VEX Robotics team BLRSAI's development of a fully autonomous robot for VEX Robotics' Tipping Point AI Competition.
Online control of the false discovery rate with decaying memory
In the online multiple testing problem, p-values corresponding to different null hypotheses are observed one by one, and the decision of whether or not to reject the current hypothesis must be made immediately, after which the next p-value is observed.
PRUNE: Preserving Proximity and Global Ranking for Network Embedding
ntumslab/PRUNE
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NeurIPS 2017
We investigate an unsupervised generative approach for network embedding.
Generating Paths with WFC
Motion plans are often randomly generated for minor game NPCs.
3D Traffic Simulation for Autonomous Vehicles in Unity and Python
Over the recent years, there has been an explosion of studies on autonomous vehicles.
Marathon Environments: Multi-Agent Continuous Control Benchmarks in a Modern Video Game Engine
Recent advances in deep reinforcement learning in the paradigm of locomotion using continuous control have raised the interest of game makers for the potential of digital actors using active ragdoll.
WONDER: Weighted one-shot distributed ridge regression in high dimensions
Here we study a fundamental and highly important problem in this area: How to do ridge regression in a distributed computing environment?
Data-driven Thresholding in Denoising with Spectral Graph Wavelet Transform
This paper is devoted to adaptive signal denoising in the context of Graph Signal Processing (GSP) using Spectral Graph Wavelet Transform (SGWT).
Bayesian posterior repartitioning for nested sampling
We show through numerical examples that this Bayesian PR (BPR) method provides a very robust, self-adapting and computationally efficient `hands-off' solution to the problem of unrepresentative priors in Bayesian inference using NS.
Making sense of sensory input
This is notable because our system is not a bespoke system designed specifically to solve intelligence tests, but a general-purpose system that was designed to make sense of any sensory sequence.
