Introducing the Separability Matrix for Error Correcting Output Codes Coding. - Miguel Ángel Bautista 001; Oriol Pujol; Xavier Baró; Sergio Escalera (MCS, 2011)

On the Design of Low Redundancy Error-Correcting Output Codes. - Miguel Ángel Bautista 001; Sergio Escalera; Xavier Baró; Oriol Pujol; Jordi Vitrià; Petia Radeva (Ensembles in Machine Learning Applications, 2011)

BoVDW: Bag-of-Visual-and-Depth-Words for gesture recognition. - Antonio Hernández-Vela; Miguel Ángel Bautista 001; Xavier Perez-Sala; Víctor Ponce-López; Xavier Baró; Oriol Pujol; Cecilio Angulo; Sergio Escalera (ICPR, 2012)

A Genetic Inspired Optimization for ECOC. - Miguel Ángel Bautista 001; Sergio Escalera; Xavier Baró; Oriol Pujol (SSPR/SPR, 2012)

Probability-Based Dynamic Time Warping for Gesture Recognition on RGB-D Data. - Miguel Ángel Bautista 001; Antonio Hernández-Vela; Víctor Ponce-López; Xavier Perez-Sala; Xavier Baró; Oriol Pujol; Cecilio Angulo; Sergio Escalera (WDIA, 2012)

Minimal design of error-correcting output codes. - Miguel Ángel Bautista 001; Sergio Escalera; Xavier Baró; Petia Radeva; Jordi Vitrià; Oriol Pujol (Pattern Recognit. Lett., 2012)

Human Body Segmentation with Multi-limb Error-Correcting Output Codes Detection and Graph Cuts Optimization. - Daniel Sánchez 005; Juan Carlos Ortega; Miguel Ángel Bautista 001; Sergio Escalera (IbPRIA, 2013)

ChaLearn Looking at People Challenge 2014: Dataset and Results. - Sergio Escalera; Xavier Baró; Jordi Gonzàlez 001; Miguel Ángel Bautista 001; Meysam Madadi; Miguel Reyes; Víctor Ponce-López; Hugo Jair Escalante; Jamie Shotton; Isabelle Guyon (ECCV Workshops (1), 2014)

Learning to Segment Humans by Stacking Their Body Parts. - Eloi Puertas; Miguel Ángel Bautista 001; Daniel Sánchez 005; Sergio Escalera; Oriol Pujol (ECCV Workshops (1), 2014)

On the design of an ECOC-Compliant Genetic Algorithm. - Miguel Ángel Bautista 001; Sergio Escalera; Xavier Baró; Oriol Pujol (Pattern Recognit., 2014)

Probability-based Dynamic Time Warping and Bag-of-Visual-and-Depth-Words for Human Gesture Recognition in RGB-D. - Antonio Hernández-Vela; Miguel Ángel Bautista 001; Xavier Perez-Sala; Víctor Ponce-López; Sergio Escalera; Xavier Baró; Oriol Pujol; Cecilio Angulo (Pattern Recognit. Lett., 2014)

ChaLearn Looking at People 2015 challenges: Action spotting and cultural event recognition. - Xavier Baró; Jordi Gonzàlez 001; Junior Fabian; Miguel Ángel Bautista 001; Marc Oliu; Hugo Jair Escalante; Isabelle Guyon; Sergio Escalera (CVPR Workshops, 2015)

HuPBA8k+: Dataset and ECOC-Graph-Cut based segmentation of human limbs. - Daniel Sánchez 005; Miguel Ángel Bautista 001; Sergio Escalera (Neurocomputing, 2015)

CliqueCNN: Deep Unsupervised Exemplar Learning. - Miguel Ángel Bautista 001; Artsiom Sanakoyeu; Ekaterina Tikhoncheva; Björn Ommer (NIPS, 2016)

A Gesture Recognition System for Detecting Behavioral Patterns of ADHD. - Miguel Ángel Bautista 001; Antonio Hernández-Vela; Sergio Escalera; Laura Igual; Oriol Pujol; Josep Moya; Verónica Violant; María Teresa Anguera (IEEE Trans. Cybern., 2016)

Deep Unsupervised Similarity Learning Using Partially Ordered Sets. - Miguel Ángel Bautista 001; Artsiom Sanakoyeu; Björn Ommer (CVPR, 2017)

Learning Where to Drive by Watching Others. - Miguel Ángel Bautista 001; Patrick Fuchs; Björn Ommer (GCPR, 2017)

Unsupervised Video Understanding by Reconciliation of Posture Similarities. - Timo Milbich; Miguel Ángel Bautista 001; Ekaterina Sutter; Björn Ommer (ICCV, 2017)

Learning to Forecast Pedestrian Intention from Pose Dynamics. - Omair Ghori; Radek Mackowiak; Miguel Ángel Bautista 001; Niklas Beuter; Lucas Drumond; Ferran Diego; Björn Ommer (Intelligent Vehicles Symposium, 2018)

Beyond one-hot encoding: Lower dimensional target embedding. - Pau Rodríguez; Miguel Ángel Bautista 001; Jordi Gonzàlez 001; Sergio Escalera (Image Vis. Comput., 2018)

Error-Correcting Factorization. - Miguel Ángel Bautista 001; Oriol Pujol; Fernando De la Torre; Sergio Escalera (IEEE Trans. Pattern Anal. Mach. Intell., 2018)

Deep unsupervised learning of visual similarities. - Artsiom Sanakoyeu; Miguel Ángel Bautista 001; Björn Ommer (Pattern Recognit., 2018)

Addressing the Loss-Metric Mismatch with Adaptive Loss Alignment. - Chen Huang 001; Shuangfei Zhai; Walter Talbott; Miguel Ángel Bautista 001; Shih-Yu Sun; Carlos Guestrin; Joshua M. Susskind (ICML, 2019)

Equivariant Neural Rendering. - Emilien Dupont; Miguel Ángel Bautista 001; Alex Colburn; Aditya Sankar; Carlos Guestrin; Josh M. Susskind; Qi Shan (CoRR, 2020)

Set Distribution Networks: a Generative Model for Sets of Images. - Shuangfei Zhai; Walter Talbott; Miguel Ángel Bautista 001; Carlos Guestrin; Josh M. Susskind (CoRR, 2020)

Unconstrained Scene Generation with Locally Conditioned Radiance Fields. - Terrance DeVries; Miguel Ángel Bautista 001; Nitish Srivastava; Graham W. Taylor; Joshua M. Susskind (ICCV, 2021)

Hypersim: A Photorealistic Synthetic Dataset for Holistic Indoor Scene Understanding. - Mike Roberts 001; Jason Ramapuram; Anurag Ranjan; Atulit Kumar; Miguel Ángel Bautista 001; Nathan Paczan; Russ Webb; Joshua M. Susskind (ICCV, 2021)

On the generalization of learning-based 3D reconstruction. - Miguel Ángel Bautista 001; Walter Talbott; Shuangfei Zhai; Nitish Srivastava; Joshua M. Susskind (WACV, 2021)

FvOR: Robust Joint Shape and Pose Optimization for Few-view Object Reconstruction. - Zhenpei Yang; Zhile Ren; Miguel Ángel Bautista 001; Zaiwei Zhang; Qi Shan; Qixing Huang (CVPR, 2022)

GAUDI: A Neural Architect for Immersive 3D Scene Generation. - Miguel Ángel Bautista 001; Pengsheng Guo; Samira Abnar; Walter Talbott; Alexander Toshev; Zhuoyuan Chen; Laurent Dinh; Shuangfei Zhai; Hanlin Goh; Daniel Ulbricht; Afshin Dehghan; Joshua M. Susskind (NeurIPS, 2022)

Fast and Explicit Neural View Synthesis. - Pengsheng Guo; Miguel Ángel Bautista 001; Alex Colburn; Liang Yang; Daniel Ulbricht; Joshua M. Susskind; Qi Shan (WACV, 2022)

f-DM: A Multi-stage Diffusion Model via Progressive Signal Transformation. - Jiatao Gu; Shuangfei Zhai; Yizhe Zhang 002; Miguel Ángel Bautista 001; Joshua M. Susskind (ICLR, 2023)

Diffusion Probabilistic Fields. - Peiye Zhuang; Samira Abnar; Jiatao Gu; Alexander G. Schwing; Joshua M. Susskind; Miguel Ángel Bautista 001 (ICLR, 2023)

Manifold Diffusion Fields. - Ahmed A. A. Elhag; Joshua M. Susskind; Miguel Ángel Bautista 001 (CoRR, 2023)

Value function estimation using conditional diffusion models for control. - Bogdan Mazoure; Walter Talbott; Miguel Ángel Bautista 001; R. Devon Hjelm; Alexander Toshev; Joshua M. Susskind (CoRR, 2023)

Is Generalized Dynamic Novel View Synthesis from Monocular Videos Possible Today? - Xiaoming Zhao 001; Alex Colburn; Fangchang Ma; Miguel Ángel Bautista 001; Joshua M. Susskind; Alexander G. Schwing (CoRR, 2023)

Adaptivity and Modularity for Efficient Generalization Over Task Complexity. - Samira Abnar; Omid Saremi; Laurent Dinh; Shantel Wilson; Miguel Ángel Bautista 001; Chen Huang 001; Vimal Thilak; Etai Littwin; Jiatao Gu; Josh M. Susskind; Samy Bengio (CoRR, 2023)

Generating Molecular Conformer Fields. - Yuyang Wang; Ahmed A. A. Elhag; Navdeep Jaitly; Joshua M. Susskind; Miguel Ángel Bautista 001 (CoRR, 2023)

CTRLorALTer: Conditional LoRAdapter for Efficient 0-Shot Control and Altering of T2I Models. - Nick Stracke; Stefan Andreas Baumann; Joshua Susskind; Miguel Ángel Bautista 001; Björn Ommer (ECCV (88), 2024)

Pseudo-Generalized Dynamic View Synthesis from a Video. - Xiaoming Zhao 001; Alex Colburn; Fangchang Ma; Miguel Ángel Bautista 001; Joshua M. Susskind; Alexander G. Schwing (ICLR, 2024)

Manifold Diffusion Fields. - Ahmed A. A. Elhag; Yuyang Wang; Joshua M. Susskind; Miguel Ángel Bautista 001 (ICLR, 2024)

Scalable Pre-training of Large Autoregressive Image Models. - Alaaeldin El-Nouby; Michal Klein; Shuangfei Zhai; Miguel Ángel Bautista 001; Vaishaal Shankar; Alexander T. Toshev; Joshua M. Susskind; Armand Joulin (ICML, 2024)

Swallowing the Bitter Pill: Simplified Scalable Conformer Generation. - Yuyang Wang; Ahmed A. A. Elhag; Navdeep Jaitly; Joshua M. Susskind; Miguel Ángel Bautista 001 (ICML, 2024)

CTRLorALTer: Conditional LoRAdapter for Efficient 0-Shot Control & Altering of T2I Models. - Nick Stracke; Stefan Andreas Baumann; Joshua M. Susskind; Miguel Ángel Bautista 001; Björn Ommer (CoRR, 2024)

World-consistent Video Diffusion with Explicit 3D Modeling. - Qihang Zhang; Shuangfei Zhai; Miguel Ángel Bautista 001; Kevin Miao; Alexander Toshev; Joshua M. Susskind; Jiatao Gu (CoRR, 2024)

Coordinate In and Value Out: Training Flow Transformers in Ambient Space. - Yuyang Wang; Anurag Ranjan; Joshua M. Susskind; Miguel Ángel Bautista 001 (CoRR, 2024)

Normalizing Flows are Capable Generative Models. - Shuangfei Zhai; Ruixiang Zhang; Preetum Nakkiran; David Berthelot; Jiatao Gu; Huangjie Zheng; Tianrong Chen; Miguel Ángel Bautista 001; Navdeep Jaitly; Joshua M. Susskind (CoRR, 2024)

3D Shape Tokenization. - Jen-Hao Rick Chang; Yuyang Wang; Miguel Ángel Bautista 001; Jiatao Gu; Joshua M. Susskind; Oncel Tuzel (CoRR, 2024)

STARFlow: Scaling Latent Normalizing Flows for High-resolution Image Synthesis. - Jiatao Gu; Tianrong Chen; David Berthelot; Huangjie Zheng; Yuyang Wang; Ruixiang Zhang; Laurent Dinh; Miguel Ángel Bautista 001; Josh M. Susskind; Shuangfei Zhai (CoRR, 2025)

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows. - Ruixiang Zhang; Shuangfei Zhai; Jiatao Gu; Yizhe Zhang 002; Huangjie Zheng; Tianrong Chen; Miguel Ángel Bautista 001; Joshua M. Susskind; Navdeep Jaitly (CoRR, 2025)