Zobrazeno 1 - 10
of 3 070
pro vyhledávání: '"P Atanasov"'
Particle flow (PFL) is an effective method for overcoming particle degeneracy, the main limitation of particle filtering. In PFL, particles are migrated towards regions of high likelihood based on the solution of a partial differential equation. Rece
Externí odkaz:
http://arxiv.org/abs/2412.09778
Autor:
Li, Runfa Blark, Suzuki, Keito, Du, Bang, Le, Ki Myung Brian, Atanasov, Nikolay, Nguyen, Truong
A signed distance function (SDF) is a useful representation for continuous-space geometry and many related operations, including rendering, collision checking, and mesh generation. Hence, reconstructing SDF from image observations accurately and effi
Externí odkaz:
http://arxiv.org/abs/2411.15468
In this paper, we derive a new Kalman filter with probabilistic data association between measurements and states. We formulate a variational inference problem to approximate the posterior density of the state conditioned on the measurement data. We v
Externí odkaz:
http://arxiv.org/abs/2411.06378
Control Strategies for Pursuit-Evasion Under Occlusion Using Visibility and Safety Barrier Functions
Autor:
Zhou, Minnan, Shaikh, Mustafa, Chaubey, Vatsalya, Haggerty, Patrick, Koga, Shumon, Panagou, Dimitra, Atanasov, Nikolay
This paper develops a control strategy for pursuit-evasion problems in environments with occlusions. We address the challenge of a mobile pursuer keeping a mobile evader within its field of view (FoV) despite line-of-sight obstructions. The signed di
Externí odkaz:
http://arxiv.org/abs/2411.01321
Autor:
Nies, L., Atanasov, D., Athanasakis-Kaklamanakis, M., Au, M., Bernerd, C., Blaum, K., Chrysalidis, K., Fischer, P., Heinke, R., Klink, C., Lange, D., Lunney, D., Manea, V., Marsh, B. A., Müller, M., Mougeot, M., Naimi, S., Schweiger, Ch., Schweikhard, L., Wienholtz, F.
Mass measurements with the ISOLTRAP mass spectrometer at CERN-ISOLDE improve mass uncertainties of neutron-deficient tin isotopes towards doubly-magic $^{100}$Sn. The mass uncertainty of $^{103}$Sn was reduced by a factor of 4, and the new value for
Externí odkaz:
http://arxiv.org/abs/2410.17995
In this work, we introduce a planning neural operator (PNO) for predicting the value function of a motion planning problem. We recast value function approximation as learning a single operator from the cost function space to the value function space,
Externí odkaz:
http://arxiv.org/abs/2410.17547
We consider neural networks (NNs) where the final layer is down-scaled by a fixed hyperparameter $\gamma$. Recent work has identified $\gamma$ as controlling the strength of feature learning. As $\gamma$ increases, network evolution changes from "laz
Externí odkaz:
http://arxiv.org/abs/2410.04642
We develop a solvable model of neural scaling laws beyond the kernel limit. Theoretical analysis of this model shows how performance scales with model size, training time, and the total amount of available data. We identify three scaling regimes corr
Externí odkaz:
http://arxiv.org/abs/2409.17858
Autor:
Long, Kehan, Parwana, Hardik, Fainekos, Georgios, Hoxha, Bardh, Okamoto, Hideki, Atanasov, Nikolay
This paper presents a novel method for modeling the shape of a continuum robot as a Neural Configuration Euclidean Distance Function (N-CEDF). By learning separate distance fields for each link and combining them through the kinematics chain, the lea
Externí odkaz:
http://arxiv.org/abs/2409.13865
Autor:
Rosati, Domenic, Edkins, Giles, Raj, Harsh, Atanasov, David, Majumdar, Subhabrata, Rajendran, Janarthanan, Rudzicz, Frank, Sajjad, Hassan
While there has been progress towards aligning Large Language Models (LLMs) with human values and ensuring safe behaviour at inference time, safety-guards can easily be removed when fine-tuned on unsafe and harmful datasets.While this setting has bee
Externí odkaz:
http://arxiv.org/abs/2409.12914