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ORCIDWonyeol Lee 0001
Person information
- affiliation: POSTECH, Pohang, South Korea
- affiliation (2023 - 2024): Carnegie Mellon University, Pittsburgh, PA, USA
- affiliation (PhD 2023): Stanford University, CA, USA
- affiliation (former): KAIST, Daejeon, South Korea
Other persons with the same name
- Wonyeol Lee 0002 — LG Display Research Labs., Paju, South Korea
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2020 – today
- 2026
[j9]Sangho Lim
, Hyoungjin Lim, Wonyeol Lee, Xavier Rival, Hongseok Yang:
Optimising Density Computations in Probabilistic Programs via Automatic Loop Vectorisation. Proc. ACM Program. Lang. 10(POPL): 597-627 (2026)- 2025
- [j8]Feras A. Saad, Wonyeol Lee:
Random Variate Generation with Formal Guarantees. Proc. ACM Program. Lang. 9(PLDI): 125-149 (2025) - [j7]Jesse Michel, Wonyeol Lee, Hongseok Yang:
Semantics of Integrating and Differentiating Singularities. Proc. ACM Program. Lang. 9(PLDI): 421-446 (2025) - [c11]Geonho Hwang, Wonyeol Lee, Yeachan Park, Sejun Park, Feras Saad:
Floating-Point Neural Networks are Provably Robust Universal Approximators. CAV (2) 2025: 301-326 - [c10]Geonho Hwang, Yeachan Park, Wonyeol Lee, Sejun Park:
Floating-Point Neural Networks Can Represent Almost All Floating-Point Functions. ICML 2025 - [i12]Geonho Hwang, Wonyeol Lee, Yeachan Park, Sejun Park, Feras Saad:
Floating-Point Neural Networks Are Provably Robust Universal Approximators. CoRR abs/2506.16065 (2025) - [i11]Feras A. Saad, Wonyeol Lee:
Random Variate Generation with Formal Guarantees. CoRR abs/2507.13494 (2025) - [i10]Sangho Lim, Hyoungjin Lim, Wonyeol Lee, Xavier Rival, Hongseok Yang:
Optimising Density Computations in Probabilistic Programs via Automatic Loop Vectorisation. CoRR abs/2511.11070 (2025) - 2024
- [j6]Yeachan Park, Geonho Hwang, Wonyeol Lee, Sejun Park:
Expressive power of ReLU and step networks under floating-point operations. Neural Networks 175: 106297 (2024) - [c9]Sejun Park, Sanghyuk Chun, Wonyeol Lee:
What does automatic differentiation compute for neural networks? ICLR 2024 - [i9]Yeachan Park, Geonho Hwang, Wonyeol Lee, Sejun Park:
Expressive Power of ReLU and Step Networks under Floating-Point Operations. CoRR abs/2401.15121 (2024) - 2023
- [j5]Wonyeol Lee, Xavier Rival, Hongseok Yang:
Smoothness Analysis for Probabilistic Programs with Application to Optimised Variational Inference. Proc. ACM Program. Lang. 7(POPL): 335-366 (2023) - [j4]Wonyeol Lee, Rahul Sharma, Alex Aiken:
Training with Mixed-Precision Floating-Point Assignments. Trans. Mach. Learn. Res. 2023 (2023) - [c8]Wonyeol Lee, Sejun Park, Alex Aiken:
On the Correctness of Automatic Differentiation for Neural Networks with Machine-Representable Parameters. ICML 2023: 19094-19140 - [i8]Wonyeol Lee, Sejun Park, Alex Aiken:
On the Correctness of Automatic Differentiation for Neural Networks with Machine-Representable Parameters. CoRR abs/2301.13370 (2023) - [i7]Wonyeol Lee, Rahul Sharma, Alex Aiken:
Training with Mixed-Precision Floating-Point Assignments. CoRR abs/2301.13464 (2023) - 2022
- [i6]Wonyeol Lee, Xavier Rival, Hongseok Yang:
Smoothness Analysis for Probabilistic Programs with Application to Optimised Variational Inference. CoRR abs/2208.10530 (2022) - 2020
- [j3]Wonyeol Lee, Hangyeol Yu, Xavier Rival, Hongseok Yang:
Towards verified stochastic variational inference for probabilistic programs. Proc. ACM Program. Lang. 4(POPL): 16:1-16:33 (2020) - [c7]Hyoungjin Lim, Gwonsoo Che, Wonyeol Lee, Hongseok Yang:
Differentiable Algorithm for Marginalising Changepoints. AAAI 2020: 4828-4835 - [c6]Wonyeol Lee, Hangyeol Yu, Xavier Rival, Hongseok Yang:
On Correctness of Automatic Differentiation for Non-Differentiable Functions. NeurIPS 2020 - [i5]Wonyeol Lee, Hangyeol Yu, Xavier Rival, Hongseok Yang:
On Correctness of Automatic Differentiation for Non-Differentiable Functions. CoRR abs/2006.06903 (2020)
2010 – 2019
- 2019
- [i4]Wonyeol Lee, Hangyeol Yu, Xavier Rival, Hongseok Yang:
Towards Verified Stochastic Variational Inference for Probabilistic Programs. CoRR abs/1907.08827 (2019) - [i3]Hyoungjin Lim, Gwonsoo Che, Wonyeol Lee, Hongseok Yang:
Differentiable Algorithm for Marginalising Changepoints. CoRR abs/1911.09839 (2019) - 2018
- [j2]Wonyeol Lee, Rahul Sharma, Alex Aiken:
On automatically proving the correctness of math.h implementations. Proc. ACM Program. Lang. 2(POPL): 47:1-47:32 (2018) - [c5]Wonyeol Lee, Hangyeol Yu, Hongseok Yang:
Reparameterization Gradient for Non-differentiable Models. NeurIPS 2018: 5558-5568 - [i2]Wonyeol Lee, Hangyeol Yu, Hongseok Yang:
Reparameterization Gradient for Non-differentiable Models. CoRR abs/1806.00176 (2018) - 2016
- [c4]Wonyeol Lee, Rahul Sharma, Alex Aiken:
Verifying bit-manipulations of floating-point. PLDI 2016: 70-84 - 2014
- [j1]Jinha Kim, Wonyeol Lee, Hwanjo Yu:
CT-IC: Continuously activated and Time-restricted Independent Cascade model for viral marketing. Knowl. Based Syst. 62: 57-68 (2014) - [c3]Wonyeol Lee, Sungwoo Park:
A proof system for separation logic with magic wand. POPL 2014: 477-490 - 2012
- [c2]Wonyeol Lee, Jinha Kim, Hwanjo Yu:
CT-IC: Continuously Activated and Time-Restricted Independent Cascade Model for Viral Marketing. ICDM 2012: 960-965 - 2011
- [i1]Wonyeol Lee, Young Woo Kim, Se Yun Kim, Jae Young Lim, Dong Hoon Lim:
Edge detection based on morphological amoebas. CoRR abs/1108.4315 (2011)
2000 – 2009
- 2009
- [c1]Wonyeol Lee, Se Yun Kim, Young Woo Kim, Jae Young Lim, Dong Hoon Lim:
Edge detection using morphological amoebas in noisy images. ICIP 2009: 2169-2172
Coauthor Index
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