6 papers
Reviving Error Correction in Modern Deep Time-Series Forecasting
Minh Hoang Nguyen, Dai Do, Huu Hiep Nguyen +3
Modern deep-learning models have achieved remarkable success in time-series forecasting. Yet, their performance degrades in long-term prediction due to error accumulation in autore…
Improving Diversity in Black-box Few-shot Knowledge Distillation
Tri-Nhan Vo, Dang Nguyen, Kien Do +1
Knowledge distillation (KD) is a well-known technique to effectively compress a large network (teacher) to a smaller network (student) with little sacrifice in performance. However…
FrameDiT: Diffusion Transformer with Matrix Attention for Efficient Video Generation
Minh Khoa Le, Kien Do, Duc Thanh Nguyen +1
High-fidelity video generation remains challenging for diffusion models due to the difficulty of modeling complex spatio-temporal dynamics efficiently. Recent video diffusion metho…
Predicting the Reliability of an Image Classifier under Image Distortion
Dang Nguyen, Sunil Gupta, Kien Do +1
In image classification tasks, deep learning models are vulnerable to image distortions i.e. their accuracy significantly drops if the input images are distorted. An image-classifi…
Finding the Trigger: Causal Abductive Reasoning on Video Events
Thao Minh Le, Vuong Le, Kien Do +3
This paper introduces a new problem, Causal Abductive Reasoning on Video Events (CARVE), which involves identifying causal relationships between events in a video and generating hy…
Learning Structural Causal Models from Ordering: Identifiable Flow Models
Minh Khoa Le, Kien Do, Truyen Tran
In this study, we address causal inference when only observational data and a valid causal ordering from the causal graph are available. We introduce a set of flow models that can…