Zobrazeno 1 - 10
of 3 932
pro vyhledávání: '"Adji A."'
Publikováno v:
Journal of Innovation and Applied Technology, Vol 9, Iss 1, Pp 12-19 (2023)
Pemungutan Pajak Bumi dan Bangunan (PBB) dalam pelaksanaannya masih terdapat permasalahan. Salah satunya di Desa Kedungsolo Porong, yaitu pencatatan dilakukan secara klasik dalam daftar buku oleh petugas desa, sehingga membutuhkan waktu lama apabila
Externí odkaz:
https://doaj.org/article/0d0c12f9bfb54e8b97e98cdc49d60b96
Large language models (LLMs) are increasingly being used in materials science. However, little attention has been given to benchmarking and standardized evaluation for LLM-based materials property prediction, which hinders progress. We present LLM4Ma
Externí odkaz:
http://arxiv.org/abs/2411.00177
Autor:
Kannen, Nithish, Ahmad, Arif, Andreetto, Marco, Prabhakaran, Vinodkumar, Prabhu, Utsav, Dieng, Adji Bousso, Bhattacharyya, Pushpak, Dave, Shachi
Text-to-Image (T2I) models are being increasingly adopted in diverse global communities where they create visual representations of their unique cultures. Current T2I benchmarks primarily focus on faithfulness, aesthetics, and realism of generated im
Externí odkaz:
http://arxiv.org/abs/2407.06863
Autor:
Yang, Yulong, Feng, Bowen, Wang, Keqin, Leonard, Naomi, Dieng, Adji Bousso, Allen-Blanchette, Christine
From pedestrians to Kuramoto oscillators, interactions between agents govern how a multitude of dynamical systems evolve in space and time. Discovering how these agents relate to each other can improve our understanding of the often complex dynamics
Externí odkaz:
http://arxiv.org/abs/2406.14746
Autor:
Li, Kangming, Rubungo, Andre Niyongabo, Lei, Xiangyun, Persaud, Daniel, Choudhary, Kamal, DeCost, Brian, Dieng, Adji Bousso, Hattrick-Simpers, Jason
Scientific machine learning (ML) endeavors to develop generalizable models with broad applicability. However, the assessment of generalizability is often based on heuristics. Here, we demonstrate in the materials science setting that heuristics based
Externí odkaz:
http://arxiv.org/abs/2406.06489
The diffusion model has shown success in generating high-quality and diverse solutions to trajectory optimization problems. However, diffusion models with neural networks inevitably make prediction errors, which leads to constraint violations such as
Externí odkaz:
http://arxiv.org/abs/2406.00990
This paper introduces alternators, a novel family of non-Markovian dynamical models for sequences. An alternator features two neural networks: the observation trajectory network (OTN) and the feature trajectory network (FTN). The OTN and the FTN work
Externí odkaz:
http://arxiv.org/abs/2405.11848
Autor:
Nguyen, Quan, Dieng, Adji Bousso
Experimental design techniques such as active search and Bayesian optimization are widely used in the natural sciences for data collection and discovery. However, existing techniques tend to favor exploitation over exploration of the search space, wh
Externí odkaz:
http://arxiv.org/abs/2405.02449
Optimal trajectory design is computationally expensive for nonlinear and high-dimensional dynamical systems. The challenge arises from the non-convex nature of the optimization problem with multiple local optima, which usually requires a global searc
Externí odkaz:
http://arxiv.org/abs/2403.05571
Autor:
Oala, Luis, Maskey, Manil, Bat-Leah, Lilith, Parrish, Alicia, Gürel, Nezihe Merve, Kuo, Tzu-Sheng, Liu, Yang, Dror, Rotem, Brajovic, Danilo, Yao, Xiaozhe, Bartolo, Max, Rojas, William A Gaviria, Hileman, Ryan, Aliment, Rainier, Mahoney, Michael W., Risdal, Meg, Lease, Matthew, Samek, Wojciech, Dutta, Debojyoti, Northcutt, Curtis G, Coleman, Cody, Hancock, Braden, Koch, Bernard, Tadesse, Girmaw Abebe, Karlaš, Bojan, Alaa, Ahmed, Dieng, Adji Bousso, Noy, Natasha, Reddi, Vijay Janapa, Zou, James, Paritosh, Praveen, van der Schaar, Mihaela, Bollacker, Kurt, Aroyo, Lora, Zhang, Ce, Vanschoren, Joaquin, Guyon, Isabelle, Mattson, Peter
Drawing from discussions at the inaugural DMLR workshop at ICML 2023 and meetings prior, in this report we outline the relevance of community engagement and infrastructure development for the creation of next-generation public datasets that will adva
Externí odkaz:
http://arxiv.org/abs/2311.13028