2025

1. Y. Bae, S. Ha, and H. Jeong, "Inferring the Langevin equation with uncertainty via Bayesian neural networks", Chaos, Solitons and Fractals, 197 116440 

2. Y. Song, Y. Bae, and H. Jeong, "Stochastic resetting mitigates latent gradient bias of SGD from label noise",  Mach. Learn.: Sci. Technol. 6 015062

3. K. Kim, E. Kwon, and Y. Baek, "Thermodynamically consistent lattice Monte Carlo method for active particles", arXiv:2503.16958,

4. V. Singh, E. Kwon, and G. J. Milburn, "Quantum thermodynamics on a limit cycle",  arXiv:2503.12118

5. E. Kwon, Y. Oh, and Y. Baek, "Phase separation of chemokinetic active particles", arXiv:2407.16676 , accepted to communications physics.

2024

1. J. Bae, Y. Baek, and H. Jeong, "Exploring how deep learning decodes anomalous diffusion via Grad-CAM", arXiv:2410.16345

2. J.-Y. Gyhm, G. Kim, H. Kwon, and Y. Baek, "Boltzmann sampling by diabatic quantum annealing", arXiv:2409.18126

3. E. Kwon, J.-M. Park, J. S. Lee, and Y. Baek "Unified hierarchical relationship between thermodynamic tradeoff relations", arXiv:2311.01098, Phys. Rev. E 110, 044131 (2024).

4. K.-W. Kim, Y. Choe, and Y. Baek, "Symmetry-breaking motility of penetrable objects in active fluids", arXiv:2304.01645, Phys. Rev. E 109, 014614 (2024).

5. E. Kwon, and Y. Baek, "α-divergence improves the entropy production estimation via machine learning", arXiv:2303.02901, Phys. Rev. E 109, 014143 (2024).

6. K. Son, Y. Choe, E. Kwon, L. G. Rigon, Y. Baek, and H.-Y. Kim, "Dynamics of self-propelled particles in vibrated dense granular media", Soft Matter 20, 2777 (2024).

2023

1. G. Kim, H. Lee, J. Jo, and Y. Baek, "Tradeoff of generalization error in unsupervised learning", arXiv:2303.05718, J. Stat. Mech.: Theor. Exp. 2023, 083401 (2023).

2. Y. Oh, and Y. Baek, "Effects of the self-propulsion parity on the efficiency of a fuel-consuming active heat engine", arXiv:2302.13870, Phys. Rev. E 108, 024602 (2023).