An Underexplored Dilemma between Confidence and Calibration in Quantized Neural Networks. - Guoxuan Xia; Sangwon Ha; Tiago Azevedo; Partha Maji (CoRR, 2021)

Augmenting Softmax Information for Selective Classification with Out-of-Distribution Data. - Guoxuan Xia; Christos-Savvas Bouganis (ACCV (6), 2022)

On the Usefulness of Deep Ensemble Diversity for Out-of-Distribution Detection. - Guoxuan Xia; Christos-Savvas Bouganis (CoRR, 2022)

Window-Based Early-Exit Cascades for Uncertainty Estimation: When Deep Ensembles are More Efficient than Single Models. - Guoxuan Xia; Christos-Savvas Bouganis (ICCV, 2023)

Logit-based ensemble distribution distillation for robust autoregressive sequence uncertainties. - Yassir Fathullah; Guoxuan Xia; Mark J. F. Gales (UAI, 2023)

Latent Diffusion Model for DNA Sequence Generation. - Zehui Li; Yuhao Ni; Tim August B. Huygelen; Akashaditya Das; Guoxuan Xia; Guy-Bart Stan; Yiren Zhao (CoRR, 2023)

Score Normalization for a Faster Diffusion Exponential Integrator Sampler. - Guoxuan Xia; Duolikun Danier; Ayan Das 005; Stathi Fotiadis; Farhang Nabiei; Ushnish Sengupta; Alberto Bernacchia (CoRR, 2023)

Absorb & Escape: Overcoming Single Model Limitations in Generating Heterogeneous Genomic Sequences. - Zehui Li; Yuhao Ni; Guoxuan Xia; William A. V. Beardall; Akashaditya Das; Guy-Bart Stan; Yiren Zhao (NeurIPS, 2024)

DiscDiff: Latent Diffusion Model for DNA Sequence Generation. - Zehui Li; Yuhao Ni; William A. V. Beardall; Guoxuan Xia; Akashaditya Das; Guy-Bart Stan; Yiren Zhao (CoRR, 2024)

Understanding Why Label Smoothing Degrades Selective Classification and How to Fix It. - Guoxuan Xia; Olivier Laurent 002; Gianni Franchi; Christos-Savvas Bouganis (CoRR, 2024)

Absorb & Escape: Overcoming Single Model Limitations in Generating Genomic Sequences. - Zehui Li; Yuhao Ni; Guoxuan Xia; William A. V. Beardall; Akashaditya Das; Guy-Bart Stan; Yiren Zhao (CoRR, 2024)

Augmenting the Softmax with Additional Confidence Scores for Improved Selective Classification with Out-of-Distribution Data. - Guoxuan Xia; Christos-Savvas Bouganis (Int. J. Comput. Vis., 2024)

Towards Understanding and Quantifying Uncertainty for Text-to-Image Generation. - Gianni Franchi; Nacim Belkhir; Dat Nguyen Trong; Guoxuan Xia; Andrea Pilzer (CVPR, 2025)

Towards Understanding Why Label Smoothing Degrades Selective Classification and How to Fix It. - Guoxuan Xia; Olivier Laurent 002; Gianni Franchi; Christos-Savvas Bouganis (ICLR, 2025)

Generative Uncertainty in Diffusion Models. - Metod Jazbec; Eliot Wong-Toi; Guoxuan Xia; Dan Zhang; Eric T. Nalisnick; Stephan Mandt (UAI, 2025)

Exploiting Mixture-of-Experts Redundancy Unlocks Multimodal Generative Abilities. - Raman Dutt; Harleen Hanspal; Guoxuan Xia; Petru-Daniel Tudosiu; Alexander Black 001; Yongxin Yang; Steven McDonagh 001; Sarah Parisot (CoRR, 2025)

A Practical Investigation of Spatially-Controlled Image Generation with Transformers. - Guoxuan Xia; Harleen Hanspal; Petru-Daniel Tudosiu; Shifeng Zhang; Sarah Parisot (CoRR, 2025)