Zobrazeno 1 - 10
of 8 144
pro vyhledávání: '"Mitrevski, A."'
Autor:
Mitrevski, Blagoj, Rak, Arina, Schnitzler, Julian, Li, Chengkun, Maksai, Andrii, Berent, Jesse, Musat, Claudiu
Digital note-taking is gaining popularity, offering a durable, editable, and easily indexable way of storing notes in a vectorized form, known as digital ink. However, a substantial gap remains between this way of note-taking and traditional pen-and-
Externí odkaz:
http://arxiv.org/abs/2402.05804
Autor:
Xu, Chenwei, Hu, Jerry Yao-Chieh, Narayanan, Aakaash, Thieme, Mattson, Nagaslaev, Vladimir, Austin, Mark, Arnold, Jeremy, Berlioz, Jose, Hanlet, Pierrick, Ibrahim, Aisha, Nicklaus, Dennis, Mitrevski, Jovan, John, Jason Michael St., Pradhan, Gauri, Saewert, Andrea, Seiya, Kiyomi, Schupbach, Brian, Thurman-Keup, Randy, Tran, Nhan, Shi, Rui, Ogrenci, Seda, Shuping, Alexis Maya-Isabelle, Hazelwood, Kyle, Liu, Han
We introduce a novel Proximal Policy Optimization (PPO) algorithm aimed at addressing the challenge of maintaining a uniform proton beam intensity delivery in the Muon to Electron Conversion Experiment (Mu2e) at Fermi National Accelerator Laboratory
Externí odkaz:
http://arxiv.org/abs/2312.17372
Autor:
Mitrevski, Alex, Plöger, Paul G.
This paper presents a modification of the data-driven sensor-based fault detection and diagnosis (SFDD) algorithm for online robot monitoring. Our version of the algorithm uses a collection of generative models, in particular restricted Boltzmann mac
Externí odkaz:
http://arxiv.org/abs/2311.13866
Autor:
Shi, R., Ogrenci, S., Arnold, J. M., Berlioz, J. R., Hanlet, P., Hazelwood, K. J., Ibrahim, M. A., Liu, H., Nagaslaev, V. P., Nicklaus, D. J., Mitrevski, J., Pradhan, G., Saewert, A. L., Schupbach, B. A., Seiya, K., Thieme, M., Thurman-Keup, R. M., Tran, N. V.
This study focuses on implementing a real-time control system for a particle accelerator facility that performs high energy physics experiments. A critical operating parameter in this facility is beam loss, which is the fraction of particles deviatin
Externí odkaz:
http://arxiv.org/abs/2311.05716
Loading of shipping containers for dairy products often includes a press-fit task, which involves manually stacking milk cartons in a container without using pallets or packaging. Automating this task with a mobile manipulator can reduce worker strai
Externí odkaz:
http://arxiv.org/abs/2307.08274
Autor:
Campos, Javier, Dong, Zhen, Duarte, Javier, Gholami, Amir, Mahoney, Michael W., Mitrevski, Jovan, Tran, Nhan
We develop an end-to-end workflow for the training and implementation of co-designed neural networks (NNs) for efficient field-programmable gate array (FPGA) and application-specific integrated circuit (ASIC) hardware. Our approach leverages Hessian-
Externí odkaz:
http://arxiv.org/abs/2304.06745
In robot-assisted therapy for individuals with Autism Spectrum Disorder, the workload of therapists during a therapeutic session is increased if they have to control the robot manually. To allow therapists to focus on the interaction with the person
Externí odkaz:
http://arxiv.org/abs/2207.12144
Robots applied in therapeutic scenarios, for instance in the therapy of individuals with Autism Spectrum Disorder, are sometimes used for imitation learning activities in which a person needs to repeat motions by the robot. To simplify the task of in
Externí odkaz:
http://arxiv.org/abs/2207.12224
Autor:
Mitrevski, Alex, Thoduka, Santosh, Sáinz, Argentina Ortega, Schöbel, Maximilian, Nagel, Patrick, Plöger, Paul G., Prassler, Erwin
Robot deployment in realistic dynamic environments is a challenging problem despite the fact that robots can be quite skilled at a large number of isolated tasks. One reason for this is that robots are rarely equipped with powerful introspection capa
Externí odkaz:
http://arxiv.org/abs/2206.12719
Autor:
Pappalardo, Alessandro, Umuroglu, Yaman, Blott, Michaela, Mitrevski, Jovan, Hawks, Ben, Tran, Nhan, Loncar, Vladimir, Summers, Sioni, Borras, Hendrik, Muhizi, Jules, Trahms, Matthew, Hsu, Shih-Chieh, Hauck, Scott, Duarte, Javier
We present extensions to the Open Neural Network Exchange (ONNX) intermediate representation format to represent arbitrary-precision quantized neural networks. We first introduce support for low precision quantization in existing ONNX-based quantizat
Externí odkaz:
http://arxiv.org/abs/2206.07527