I am a Postdoctoral Associate at CMU CSD working with Feras Saad. I received a Ph.D. degree in Computer Science from Stanford University, where I was advised by Alex Aiken and supported by Samsung Scholarship. In 2017-2020, I was a researcher at KAIST to serve military service. I received a B.S. degree in Computer Science & Mathematics from POSTECH.
My research aims to broaden our theoretical understanding of continuous computations performed in practice and provide practical implications based on it. I am particularly interested in studying various gaps between the theory and practice of continuous computations and analyzing the correctness of these computations under these gaps.
Correctness (provable guarantee | verification | program analysis)
Continuous Computation (finite-precision | differentiable | probabilistic)
Finite Precision (floating point | elementary function | low precision)
Differentiation (non-differentiability | automatic differentiation | gradient estimation)
Probabilistic Inference (variational inference)
What Does Automatic Differentiation Compute for Neural Networks?
Sejun Park, Sanghyuk Chun, Wonyeol Lee
Submitted, 2023
Reasoning About Floating Point in Real-World Systems
Wonyeol Lee
Ph.D. Dissertation, 2023
slides
On the Correctness of Automatic Differentiation for Neural Networks with Machine-Representable Parameters
Wonyeol Lee, Sejun Park, Alex Aiken
ICML 2023
slides
Training with Mixed-Precision Floating-Point Assignments
Wonyeol Lee, Rahul Sharma, Alex Aiken
TMLR 2023
code
Smoothness Analysis for Probabilistic Programs with Application to Optimised Variational Inference
Wonyeol Lee, Xavier Rival, Hongseok Yang
POPL 2023
slides
| video
| code
On Correctness of Automatic Differentiation for Non-Differentiable Functions
Wonyeol Lee, Hangyeol Yu, Xavier Rival, Hongseok Yang
NeurIPS 2020
(Spotlight)
slides
(long)
| video
Differentiable Algorithm for Marginalising Changepoints
Hyoungjin Lim, Gwonsoo Che, Wonyeol Lee, Hongseok Yang
AAAI 2020
Towards Verified Stochastic Variational Inference for Probabilistic Programs
Wonyeol Lee, Hangyeol Yu, Xavier Rival, Hongseok Yang
POPL 2020
slides
| video
| code
Reparameterization Gradient for Non-Differentiable Models
Wonyeol Lee, Hangyeol Yu, Hongseok Yang
NeurIPS 2018
slides
| code
On Automatically Proving the Correctness of math.h
Implementations
Wonyeol Lee, Rahul Sharma, Alex Aiken
POPL 2018
slides
(short)
| video
Verifying Bit-Manipulations of Floating-Point
Wonyeol Lee, Rahul Sharma, Alex Aiken
PLDI 2016
slides
| video
A Proof System for Separation Logic with Magic Wand
Wonyeol Lee, Sungwoo Park
POPL 2014
CT-IC: Continuously Activated and Time-Restricted Independent Cascade Model for Viral Marketing
Wonyeol Lee, Jinha Kim, Hwanjo Yu
ICDM 2012
journal
| slides
Edge Detection Using Morphological Amoebas in Noisy Images
Wonyeol Lee, Seyun Kim, Youngwoo Kim, Jaeyoung Lim, Dong Hoon Lim
ICIP 2009
journal