Geonho Hwang

According to our database, Geonho Hwang authored at least 22 papers between 2020 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

Expressive Power of Floating-Point Neural Networks with Arbitrary Reduction Orders and Inexact Activation Implementations.

Yeachan Park, Geonho Hwang, Wonyeol Lee, Sejun Park

CoRR, May, 2026

Floating-Point Networks with Automatic Differentiation Can Represent Almost All Floating-Point Functions and Their Gradients.

Sejun Park, Yeachan Park, Geonho Hwang

CoRR, May, 2026

On the Expressive Power of Floating-Point Transformers.

Sejun Park, Yeachan Park, Geonho Hwang

CoRR, January, 2026

2025

Localized Estimation of Condition Numbers for MILU Preconditioners on a Graph.

Geonho Hwang, Yesom Park, Yueun Lee, Jooyoung Hahn, Myungjoo Kang

CoRR, January, 2025

Analyzing the latent space of GAN through local dimension estimation for disentanglement evaluation.

Jaewoong Choi, Geonho Hwang, Hyunsoo Cho, Myungjoo Kang

Pattern Recognit., 2025

Optimal Minimum Width for the Universal Approximation of Continuously Differentiable Functions by Deep Narrow MLPs.

Geonho Hwang

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

Minimum Width for Deep, Narrow MLP: A Diffeomorphism Approach.

Geonho Hwang

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

Minimum Width for Universal Approximation using Squashable Activation Functions.

Jonghyun Shin, Namjun Kim, Geonho Hwang, Sejun Park

Proceedings of the Forty-second International Conference on Machine Learning, 2025

Floating-Point Neural Networks Can Represent Almost All Floating-Point Functions.

Geonho Hwang, Yeachan Park, Wonyeol Lee, Sejun Park

Proceedings of the Forty-second International Conference on Machine Learning, 2025

Floating-Point Neural Networks are Provably Robust Universal Approximators.

Geonho Hwang, Wonyeol Lee, Yeachan Park, Sejun Park, Feras Saad

Proceedings of the Computer Aided Verification - 37th International Conference, 2025

2024

Expressive power of ReLU and step networks under floating-point operations.

Yeachan Park, Geonho Hwang, Wonyeol Lee, Sejun Park

Neural Networks, 2024

Analysis of efficient preconditioner for solving Poisson equation with Dirichlet boundary condition in irregular three-dimensional domains.

Geonho Hwang, Yesom Park, Yueun Lee, Myungjoo Kang

J. Comput. Phys., 2024

On Expressive Power of Quantized Neural Networks under Fixed-Point Arithmetic.

Geonho Hwang, Yeachan Park, Sejun Park

CoRR, 2024

2023

Disentangling the correlated continuous and discrete generative factors of data.

Jaewoong Choi, Geonho Hwang, Myungjoo Kang

Pattern Recognit., 2023

Minimal Width for Universal Property of Deep RNN.

Changhoon Song, Geonho Hwang, Junho Lee, Myungjoo Kang

J. Mach. Learn. Res., 2023

Minimum Width for Deep, Narrow MLP: A Diffeomorphism and the Whitney Embedding Theorem Approach.

Geonho Hwang

CoRR, 2023

MAGANet: Achieving Combinatorial Generalization by Modeling a Group Action.

Geonho Hwang, Jaewoong Choi, Hyunsoo Cho, Myungjoo Kang

Proceedings of the International Conference on Machine Learning, 2023

Finding the Global Semantic Representation in GAN through Fréchet Mean.

Jaewoong Choi, Geonho Hwang, Hyunsoo Cho, Myungjoo Kang

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Universal Property of Convolutional Neural Networks.

Geonho Hwang, Myungjoo Kang

CoRR, 2022

Analyzing the Latent Space of GAN through Local Dimension Estimation.

Jaewoong Choi, Geonho Hwang, Hyunsoo Cho, Myungjoo Kang

CoRR, 2022

Do Not Escape From the Manifold: Discovering the Local Coordinates on the Latent Space of GANs.

Jaewoong Choi, Junho Lee, Changyeon Yoon, Jung Ho Park, Geonho Hwang, Myungjoo Kang

Proceedings of the Tenth International Conference on Learning Representations, 2022

2020

Discond-VAE: Disentangling Continuous Factors from the Discrete.

Jaewoong Choi, Geonho Hwang, Myungjoo Kang

CoRR, 2020