Zobrazeno 1 - 10
of 21
pro vyhledávání: '"Siemenn, Alexander E."'
Integrating autonomous contact-based robotic characterization into self-driving laboratories can enhance measurement quality, reliability, and throughput. While deep learning models support robust autonomy, current methods lack pixel-precision positi
Externí odkaz:
http://arxiv.org/abs/2411.09892
Bayesian optimization (BO) suffers from long computing times when processing highly-dimensional or large data sets. These long computing times are a result of the Gaussian process surrogate model having a polynomial time complexity with the number of
Externí odkaz:
http://arxiv.org/abs/2309.04510
Autor:
Siemenn, Alexander E., Aissi, Eunice, Sheng, Fang, Tiihonen, Armi, Kavak, Hamide, Das, Basita, Buonassisi, Tonio
High-throughput materials synthesis methods have risen in popularity due to their potential to accelerate the design and discovery of novel functional materials, such as solution-processed semiconductors. After synthesis, key material properties must
Externí odkaz:
http://arxiv.org/abs/2304.14408
Autor:
Petsiuk, Vitali, Siemenn, Alexander E., Surbehera, Saisamrit, Chin, Zad, Tyser, Keith, Hunter, Gregory, Raghavan, Arvind, Hicke, Yann, Plummer, Bryan A., Kerret, Ori, Buonassisi, Tonio, Saenko, Kate, Solar-Lezama, Armando, Drori, Iddo
We provide a new multi-task benchmark for evaluating text-to-image models. We perform a human evaluation comparing the most common open-source (Stable Diffusion) and commercial (DALL-E 2) models. Twenty computer science AI graduate students evaluated
Externí odkaz:
http://arxiv.org/abs/2211.12112
Autor:
Siemenn, Alexander E.
Functional materials have vast and high-dimensional compositions spaces which make discovering optimized compositions intractable with conventional synthesis tools. Conventional experimental methods of exploring material composition spaces are slow a
Publikováno v:
npj Comput Mater 9, 79 (2023)
Needle-in-a-Haystack problems exist across a wide range of applications including rare disease prediction, ecological resource management, fraud detection, and material property optimization. A Needle-in-a-Haystack problem arises when there is an ext
Externí odkaz:
http://arxiv.org/abs/2208.13771
Autor:
Siemenn, Alexander E., Shaulsky, Evyatar, Beveridge, Matthew, Buonassisi, Tonio, Hashmi, Sara M., Drori, Iddo
Generating droplets from a continuous stream of fluid requires precise tuning of a device to find optimized control parameter conditions. It is analytically intractable to compute the necessary control parameter values of a droplet-generating device
Externí odkaz:
http://arxiv.org/abs/2105.13553
High-performance semiconductor optoelectronics such as perovskites have high-dimensional and vast composition spaces that govern the performance properties of the material. To cost-effectively search these composition spaces, we utilize a high-throug
Externí odkaz:
http://arxiv.org/abs/2105.02858
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