HAPNEST: an efficient tool for generating large-scale genetics datasets from limited training data

Sophie Wharrie; Zhiyu Yang; Vishnu Raj; Remo Monti; Rahul Gupta; Ying Wang; Alicia Martin; Luke J O'Connor; Samuel Kaski; Pekka Marttinen; Pier Francesco Palamara; Christoph Lippert; Andrea Ganna

HAPNEST: an efficient tool for generating large-scale genetics datasets from limited training data

Sophie Wharrie, Zhiyu Yang, Vishnu Raj, Remo Monti, Rahul Gupta, Ying Wang, Alicia Martin, Luke J O'Connor, Samuel Kaski, Pekka Marttinen, Pier Francesco Palamara, Christoph Lippert, Andrea Ganna

Research output: Contribution to conference › Abstract › Scientific › peer-review

Original language	English
Publication status	Published - 2022
MoE publication type	Not Eligible
Event	NeurIPS Workshop on Synthetic Data for Empowering ML Research - New Orleans, United States Duration: 2 Dec 2022 → 2 Dec 2022 https://www.syntheticdata4ml.vanderschaar-lab.com/

Workshop

Workshop	NeurIPS Workshop on Synthetic Data for Empowering ML Research
Abbreviated title	SyntheticData4ML
Country/Territory	United States
City	New Orleans
Period	02/12/2022 → 02/12/2022
Internet address	https://www.syntheticdata4ml.vanderschaar-lab.com/

Access to Document

https://openreview.net/forum?id=zW6XoC-v6_D

Cite this

Wharrie, S., Yang, Z., Raj, V., Monti, R., Gupta, R., Wang, Y., Martin, A., O'Connor, L. J., Kaski, S., Marttinen, P., Palamara, P. F., Lippert, C., & Ganna, A. (2022). HAPNEST: an efficient tool for generating large-scale genetics datasets from limited training data. Abstract from NeurIPS Workshop on Synthetic Data for Empowering ML Research, New Orleans, Louisiana, United States. https://openreview.net/forum?id=zW6XoC-v6_D

@conference{0a4b45ddb7624489bf6c9e8afdca85d3,

title = "HAPNEST: an efficient tool for generating large-scale genetics datasets from limited training data",

author = "Sophie Wharrie and Zhiyu Yang and Vishnu Raj and Remo Monti and Rahul Gupta and Ying Wang and Alicia Martin and O'Connor, {Luke J} and Samuel Kaski and Pekka Marttinen and Palamara, {Pier Francesco} and Christoph Lippert and Andrea Ganna",

year = "2022",

language = "English",

note = "NeurIPS Workshop on Synthetic Data for Empowering ML Research, SyntheticData4ML ; Conference date: 02-12-2022 Through 02-12-2022",

url = "https://www.syntheticdata4ml.vanderschaar-lab.com/",

}

Wharrie, S, Yang, Z, Raj, V, Monti, R, Gupta, R, Wang, Y, Martin, A, O'Connor, LJ, Kaski, S , Marttinen, P, Palamara, PF, Lippert, C & Ganna, A 2022, 'HAPNEST: an efficient tool for generating large-scale genetics datasets from limited training data', NeurIPS Workshop on Synthetic Data for Empowering ML Research, New Orleans, United States, 02/12/2022 - 02/12/2022. <https://openreview.net/forum?id=zW6XoC-v6_D>

TY - CONF

T1 - HAPNEST: an efficient tool for generating large-scale genetics datasets from limited training data

AU - Wharrie, Sophie

AU - Yang, Zhiyu

AU - Raj, Vishnu

AU - Monti, Remo

AU - Gupta, Rahul

AU - Wang, Ying

AU - Martin, Alicia

AU - O'Connor, Luke J

AU - Kaski, Samuel

AU - Marttinen, Pekka

AU - Palamara, Pier Francesco

AU - Lippert, Christoph

AU - Ganna, Andrea

PY - 2022

Y1 - 2022

M3 - Abstract

T2 - NeurIPS Workshop on Synthetic Data for Empowering ML Research

Y2 - 2 December 2022 through 2 December 2022

ER -