Abdul Fatir Ansari

According to our database, Abdul Fatir Ansari authored at least 15 papers between 2016 and 2024.

Collaborative distances:

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

2024

Enhancing Foundation Models for Time Series Forecasting via Wavelet-based Tokenization.

Luca Masserano, Abdul Fatir Ansari, Boran Han, Xiyuan Zhang, Christos Faloutsos, Michael W. Mahoney, Andrew Gordon Wilson, Youngsuk Park, Syama Sundar Rangapuram, Danielle C. Maddix, Yuyang Wang

CoRR, 2024

Hard Constraint Guided Flow Matching for Gradient-Free Generation of PDE Solutions.

Chaoran Cheng, Boran Han, Danielle C. Maddix, Abdul Fatir Ansari, Andrew Stuart, Michael W. Mahoney, Yuyang Wang

CoRR, 2024

Comparing and Contrasting Deep Learning Weather Prediction Backbones on Navier-Stokes and Atmospheric Dynamics.

Matthias Karlbauer, Danielle C. Maddix, Abdul Fatir Ansari, Boran Han, Gaurav Gupta, Yuyang Wang, Andrew Stuart, Michael W. Mahoney

CoRR, 2024

Chronos: Learning the Language of Time Series.

Abdul Fatir Ansari, Lorenzo Stella, Ali Caner Türkmen, Xiyuan Zhang, Pedro Mercado, Huibin Shen, Oleksandr Shchur, Syama Sundar Rangapuram, Sebastian Pineda-Arango, Shubham Kapoor, Jasper Zschiegner, Danielle C. Maddix, Michael W. Mahoney, Kari Torkkola, Andrew Gordon Wilson, Michael Bohlke-Schneider, Yuyang Wang

CoRR, 2024

Generative Modeling with Flow-Guided Density Ratio Learning.

Alvin Heng, Abdul Fatir Ansari, Harold Soh

Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2024

2023

Predict, Refine, Synthesize: Self-Guiding Diffusion Models for Probabilistic Time Series Forecasting.

Marcel Kollovieh, Abdul Fatir Ansari, Michael Bohlke-Schneider, Jasper Zschiegner, Hao Wang, Yuyang Wang

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Neural Continuous-Discrete State Space Models for Irregularly-Sampled Time Series.

Abdul Fatir Ansari, Alvin Heng, Andre Lim, Harold Soh

Proceedings of the International Conference on Machine Learning, 2023

2021

Deep Explicit Duration Switching Models for Time Series.

Abdul Fatir Ansari, Konstantinos Benidis, Richard Kurle, Ali Caner Türkmen, Harold Soh, Alexander J. Smola, Bernie Wang, Tim Januschowski

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Refining Deep Generative Models via Discriminator Gradient Flow.

Abdul Fatir Ansari, Ming Liang Ang, Harold Soh

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

Refining Deep Generative Models via Wasserstein Gradient Flows.

Abdul Fatir Ansari, Ming Liang Ang, Harold Soh

CoRR, 2020

Event-Driven Visual-Tactile Sensing and Learning for Robots.

Tasbolat Taunyazov, Weicong Sng, Brian Lim, Hian-Hian See, Jethro Kuan, Abdul Fatir Ansari, Benjamin C. K. Tee, Harold Soh

Proceedings of the Robotics: Science and Systems XVI, 2020

A Characteristic Function Approach to Deep Implicit Generative Modeling.

Abdul Fatir Ansari, Jonathan Scarlett, Harold Soh

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2019

Hyperprior Induced Unsupervised Disentanglement of Latent Representations.

Abdul Fatir Ansari, Harold Soh

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

Exercise classification and event segmentation in Hammersmith Infant Neurological Examination videos.

Abdul Fatir Ansari, Partha Pratim Roy, Debi Prosad Dogra

Mach. Vis. Appl., 2018

2016

Posture Recognition in HINE Exercises.

Abdul Fatir Ansari, Partha Pratim Roy, Debi Prosad Dogra

Proceedings of International Conference on Computer Vision and Image Processing, 2016