Zobrazeno 1 - 10
of 3 260
pro vyhledávání: '"Hoffman, A. C. A."'
Autor:
Ross, Jerret, Belgodere, Brian, Hoffman, Samuel C., Chenthamarakshan, Vijil, Mroueh, Youssef, Das, Payel
Transformer-based models trained on large and general purpose datasets consisting of molecular strings have recently emerged as a powerful tool for successfully modeling various structure-property relations. Inspired by this success, we extend the pa
Externí odkaz:
http://arxiv.org/abs/2405.04912
Autor:
Nagireddy, Manish, Singh, Moninder, Hoffman, Samuel C., Ju, Evaline, Ramamurthy, Karthikeyan Natesan, Varshney, Kush R.
Ensuring trustworthiness in machine learning (ML) models is a multi-dimensional task. In addition to the traditional notion of predictive performance, other notions such as privacy, fairness, robustness to distribution shift, adversarial robustness,
Externí odkaz:
http://arxiv.org/abs/2302.09190
Autor:
Feffer, Michael, Hirzel, Martin, Hoffman, Samuel C., Kate, Kiran, Ram, Parikshit, Shinnar, Avraham
Bias mitigators can improve algorithmic fairness in machine learning models, but their effect on fairness is often not stable across data splits. A popular approach to train more stable models is ensemble learning, but unfortunately, it is unclear ho
Externí odkaz:
http://arxiv.org/abs/2210.05594
Autor:
Hoffman, Samuel C., Das, Payel, Shanmugam, Karthikeyan, Wadhawan, Kahini, Sattigeri, Prasanna
Training generative models that capture rich semantics of the data and interpreting the latent representations encoded by such models are very important problems in un-/self-supervised learning. In this work, we provide a simple algorithm that relies
Externí odkaz:
http://arxiv.org/abs/2207.07174
Autor:
Manica, Matteo, Born, Jannis, Cadow, Joris, Christofidellis, Dimitrios, Dave, Ashish, Clarke, Dean, Teukam, Yves Gaetan Nana, Giannone, Giorgio, Hoffman, Samuel C., Buchan, Matthew, Chenthamarakshan, Vijil, Donovan, Timothy, Hsu, Hsiang Han, Zipoli, Federico, Schilter, Oliver, Kishimoto, Akihiro, Hamada, Lisa, Padhi, Inkit, Wehden, Karl, McHugh, Lauren, Khrabrov, Alexy, Das, Payel, Takeda, Seiji, Smith, John R.
Publikováno v:
Nature Partner Journals (npj) Computational Materials 9, 69 (2023)
With the growing availability of data within various scientific domains, generative models hold enormous potential to accelerate scientific discovery. They harness powerful representations learned from datasets to speed up the formulation of novel hy
Externí odkaz:
http://arxiv.org/abs/2207.03928
Autor:
Chenthamarakshan, Vijil, Hoffman, Samuel C., Owen, C. David, Lukacik, Petra, Strain-Damerell, Claire, Fearon, Daren, Malla, Tika R., Tumber, Anthony, Schofield, Christopher J., Duyvesteyn, Helen M. E., Dejnirattisai, Wanwisa, Carrique, Loic, Walter, Thomas S., Screaton, Gavin R., Matviiuk, Tetiana, Mojsilovic, Aleksandra, Crain, Jason, Walsh, Martin A., Stuart, David I., Das, Payel
The discovery of novel inhibitor molecules for emerging drug-target proteins is widely acknowledged as a challenging inverse design problem: Exhaustive exploration of the vast chemical search space is impractical, especially when the target structure
Externí odkaz:
http://arxiv.org/abs/2204.09042
Autor:
Stokes, Jamesa L., Presby, Michael J., Hoffman, Leland C., Setlock, John A., Salem, Jonathan A., Harder, Bryan J.
Publikováno v:
In Surface & Coatings Technology 30 October 2024 494 Part 1
Autor:
Feffer, Michael, Hirzel, Martin, Hoffman, Samuel C., Kate, Kiran, Ram, Parikshit, Shinnar, Avraham
There are several bias mitigators that can reduce algorithmic bias in machine learning models but, unfortunately, the effect of mitigators on fairness is often not stable when measured across different data splits. A popular approach to train more st
Externí odkaz:
http://arxiv.org/abs/2202.00751
Autor:
Hoffman, Samuel C., Chenthamarakshan, Vijil, Zubarev, Dmitry Yu., Sanders, Daniel P., Das, Payel
Photo-acid generators (PAGs) are compounds that release acids ($H^+$ ions) when exposed to light. These compounds are critical components of the photolithography processes that are used in the manufacture of semiconductor logic and memory chips. The
Externí odkaz:
http://arxiv.org/abs/2112.01625
Autor:
Hoffman, Joel C., Hollenhorst, Tom, Peterson, Greg, Launspach, Jonathon, Coffman, Ellen, Burkhard, Lawrence
Publikováno v:
In Marine Pollution Bulletin December 2024 209 Part B