Optical Experiment
Optical experiments encompass a broad range of research employing light-based techniques to investigate diverse phenomena, from urban planning and traffic flow optimization to satellite navigation and fundamental physics. Current research emphasizes the application of machine learning, particularly deep learning models and reinforcement learning algorithms, to analyze experimental data, optimize experimental design, and improve the efficiency of simulations. These advancements are significantly impacting various fields, enabling more efficient data analysis, improved decision-making in complex systems, and the development of novel technologies in areas such as autonomous systems and space exploration.
Papers
Experiments in Adaptive Replanning for Fast Autonomous Flight in Forests
Laura Jarin-Lipschitz, Xu Liu, Yuezhan Tao, Vijay Kumar
Practical Recommendations for the Design of Automatic Fault Detection Algorithms Based on Experiments with Field Monitoring Data
Eduardo Abdon Sarquis Filho, Björn Müller, Nicolas Holland, Christian Reise, Klaus Kiefer, Bernd Kollosch, Paulo J. Costa Branco
Enabling Reproducibility and Meta-learning Through a Lifelong Database of Experiments (LDE)
Jason Tsay, Andrea Bartezzaghi, Aleke Nolte, Cristiano Malossi
RuCLIP -- new models and experiments: a technical report
Alex Shonenkov, Andrey Kuznetsov, Denis Dimitrov, Tatyana Shavrina, Daniil Chesakov, Anastasia Maltseva, Alena Fenogenova, Igor Pavlov, Anton Emelyanov, Sergey Markov, Daria Bakshandaeva, Vera Shybaeva, Andrey Chertok