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The work of David Mumford
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Scientific text mining
Multimodal learning and reasoning
Selected papers in CoRL
Valiant's work on AI/ML
Connectionism: A review
Recursive thinking
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AI in the next 20 years
AI/ML for climate change
AI in the 2010s and 2020s
Intelligience priors
Free energy principle
World models
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Sample efficient learning
Energy eficient AI

 


 

Reading Club on Differentiable AI

Time: Thursday, 3-4.5PM
Location: NA1.421 Waurn Ponds Campus & Zoom

Schedule
09/01/2025: The shifting landscape of AI, part II (Truyen Tran)
02/01/2025: -------HOLIDAY-------------
26/12/2024: -------HOLIDAY-------------
19/12/2024: ML for materials science - Tentative (Duc-Anh Dao, @JAIST Japan)
12/12/2024: AI for physics - tentative (Dr Nguyen, Tuan-Hung @MIT & Tohoku Uni)
05/12/2024: 3D vision-language understanding (Quang-Hung Le)
28/11/2024: Flow matching in Diffusion Models (Khanh-Toan Nguyen)
21/11/2024: Optimal causal trajectory modelling (Phuoc Nguyen)
14/11/2024: Prompt tuning for black-box LLMs (Giang Ngo)
07/11/2024: Sequence modeling in RL (Minh-Hoang Nguyen)
31/10/2024: Assessing hallucinations and uncertainty in LLMs (Hung Le)
24/10/2024: Quaternions modules for materials science (Linh La)
17/10/2024: Diffusion models for image-to-image (Duc Kieu)
10/10/2024: Inference time alignment learning for language models (Dai Do)
03/10/2024: -------CANCELLED--------------
26/09/2024: SAM2: Promptable segmentation of image and video (Xuan-Tuyen Tran)
19/09/2024: Online test-time adaptation (Thong Bach)
12/09/2024: Multimodal Theory of Mind (Dung Nguyen)
05/09/2024: The materials alchemist: building a material discovery ecosystem (Sherif Tawfik Abbas)
29/08/2024: Black-box data-free knowledge distillation (Tri-Nhan Vo)
22/08/2024: Lifting the limit of Multimodal LLMs (Tri Nguyen)
18/07/2024: -------POSTPONED--------------
08/08/2024: Discrete diffusion models (Kien Do)
01/08/2024: Lifelong learning for LLMs (Tuan Hoang)
25/07/2024: Visual reasoning via LLM programmers (Thao Le)
18/07/2024: -------POSTPONED--------------
11/07/2024: KAN: Kolmogorov-Arnold Networks (Ragja Palakkadavath)
04/07/2024: Advances in Sparse Mixture of Experts (Giang Do)
27/06/2024: Foundation models for human motion (Romeo Morais)
20/06/2024: Causal normalizing flow (Khoa Le)
13/06/2024: -------CANCELLED--------------
06/06/2024: Hallucination in Large Vision Language Models (Quang-Hung Le)
30/05/2024: Denoising diffusion (Phuoc Nguyen)
23/05/2024: Transfer learning for graphs using Gaussian Processes (Giang Ngo)
16/05/2024: Guidance in diffusion models (Khanh-Toan Nguyen)
09/05/2024: Multimodal Agents (Quan Nguyen @Ontocord.ai)
02/05/2024: Human-aligned LLMs (Hung Le)
25/4/2024: -------ANZAC Day-------------
18/04/2024: Causality for Offline RL (Minh-Hoang Nguyen)
11/04/2024: Autonomous agents (Quy Nguyen)
04/04/2024: Stability of Physics-informed Neural Networks (Kha Pham)
28/03/2024: Prompt optimization methods for LLMs (Dai Do)
21/03/2024: Prompts for visual in-context learning (Xuan-Tuyen Tran)
14/03/2024: LLM-based multi-agents (Dung Nguyen)
07/03/2024: Physics-informed GNN for materials (Sherif Tawfik Abbas)
29/02/2024: Knowledge distillation with proxy data (Tri-Nhan Vo)
22/02/2024: LLMs for scientific discovery (Tri Nguyen)
15/02/2024: Diffusion models for image editing (Kien Do)
08/02/2024: 3D reconstruction (Tuan Hoang)
01/02/2024: Advances in vision-language learning (Thao Le)
25/01/2024: Distribution shift by label noise (Ragja Palakkadavath)
18/01/2024: Visual prompting 2 (Romero Morais)
11/01/2024: GenAI: Shifting the AI landscape, part I (Truyen Tran)
04/01/2024: -------HOLIDAY-------------
28/12/2023: -------HOLIDAY-------------
21/12/2023: Advances in causal representation learning (Khoa Le)
14/12/2023: Modern ML for tabular data (Quang-Hung Le)
07/12/2023: Causality in LLMs (Phuoc Nguyen)
30/11/2023: Fast Gaussian processes (Giang Ngo)
23/11/2023: Backtracking counterfactuals (Khanh-Toan Nguyen)
16/11/2023: Emerging abilities in LLMs (Hung Le)
09/11/2023: Physics-informed machine learning 3 (Minh-Thang Nguyen)
02/11/2023: Sample efficiency in RL with causality (Minh-Hoang Nguyen)
26/10/2023: In-context learning (Kha Pham)
19/10/2023: Long form video understanding (Xuan-Tuyen Tran)
12/10/2023: Modelling other agents, cont. (Dung Nguyen)
05/10/2023: -------POSTPONED--------------
28/09/2023: Using language to build world models (Thommen George)
21/09/2023: Sample-efficient GANs for knowledge distillation  (Tri-Nhan Vo)
14/09/2023: Advances in robotics with LLMs (Laknath Semage)
07/09/2023: Adversarial attack on language and vision models (Kien Do)
31/08/2023: Temporal grounding in video (Thao Le)
24/08/2023: -------POSTPONED--------------
17/08/2023: TikTok video duplication detection (Tuan Hoang)
10/08/2023: AI for material science (Tri Nguyen)
03/08/2023: Training and inferencing LLMs (Duy-Hung Tran)
27/07/2023: Fairness in deep learning (Ragja Palakkadavath)
20/07/2023: Active learning + model selection (Romero Morais)
13/07/2023: Root cause analysis (Phuoc Nguyen)
06/07/2023: Robust LLMs (Giang Ngo)
29/06/2023: Causal machine learning (Khanh-Toan Nguyen)
22/06/2023: Limitations of LLMs (Long Dang)
15/06/2023: -------CANCELLED--------------
08/06/2023: Foundation Models for Science (Truyen Tran)
01/06/2023: Language-guided exploration in RL (Hung Le)
25/05/2023: Longitudinal healthcare modelling (Nikolaj Holm)
18/05/2023: AI for science (Kha Pham)
11/05/2023: Visual prompting (Xuan-Tuyen Tran)
04/05/2023: Multiagent inverse RL via ToM reasoning (Dung Nguyen)
27/04/2023: Physics-informed machine learning 2 (Minh-Thang Nguyen)
20/04/2023: Influencing human behaviours with offline RL (Thommen George)
13/04/2023: -------POSTPONED--------------
06/04/2023: Diffusion probabilistic models: Variational perspective (Kien Do)
30/03/2023: Action transformation (Laknath Semage)
23/03/2023: ChatGPT (Duy-Hung Tran)
16/03/2023: Visual abductive reasoning (Thao Le)
09/03/2023: Generative Flow Networks 2 (Tri Nguyen)
02/03/2023: Continual learning (Tuan Hoang)
23/02/2023: Forward forward networks (Tri-Nhan Vo)
16/02/2023: Video moment retrieval (Hoang-Anh Pham)
09/02/2023: Representations for domain generalisation (Ragja Palakkadavath)
02/02/2023: Representation learning for human skeleton (Romero Morais)
26/01/2023:  -------HOLIDAY-------------
19/01/2023: Diffusion models 2 (Phuoc Nguyen)
12/01/2023: Expressiveness of GNNs (Giang Ngo)
05/01/2023: -------HOLIDAY-------------
29/12/2022: -------HOLIDAY-------------
22/12/2022: -------HOLIDAY-------------
15/12/2022: Feature learning via causal inference (Khanh-Toan Nguyen)
08/12/2022: Scene understanding (Long Dang)
01/12/2022: Trust region optimization in RL (Hung Le)
24/11/2022: Abstraction and generalization (Kha Pham)
17/11/2022: Vision Transformer vs CNN (Xuan-Tuyen Tran)
10/11/2022: Theory of mind (cont.) (Dung Nguyen)
03/11/2022: Reward-relational feedback (Thommen George)
27/10/2022: -------POSTPONED--------------
20/10/2022: Out-of-distribution detection (Kien Do)
13/10/2022: Flow Network based Generative Models (Tri Nguyen)
06/10/2022: Task planning with large language models & RL (Laknath Semage)
29/09/2022: Diffusion models 1 (Duy-Hung Tran)
22/09/2022: -------HOLIDAY-------------
15/09/2022: Data encoding for quantum ML 2 (Minh-Thang Nguyen)
08/09/2022: Post-deep learning era (3) (Truyen Tran)
01/09/2022: Post-deep learning era (2) (Truyen Tran)
25/08/2022: Post-deep learning era (1) (Truyen Tran)
18/08/2022: -------CANCELLED--------------
11/08/2022: -------CANCELLED--------------
04/08/2022: Actor centric in video understanding (Thao Le)
28/07/2022: Causal knowledge for O.O.D generalisation (Romero Morais)
21/07/2022: Unsupervised object-centric segmentation (Hoang-Anh Pham)
14/07/2022: Theory of mind (cont.) (Dung Nguyen)
07/07/2022: (Tutorial) Bayesian neural networks (Phuoc Nguyen)
30/06/2022: (Tutorial) Variational inference & generative models (Hung Le)
23/06/2022: Analogy in AI (Kha Pham)
16/06/2022: Efficient preference based RL (Thommen George)
09/06/2022: -------CANCELLED--------------
02/06/2022: Generalist AI (Truyen Tran)
26/05/2022: Deep causal inference (Kien Do)
19/05/2022: Tokenisation (Vuong Le)
12/05/2022: -------CANCELLED--------------
05/05/2022: Knowledge graph - augmented language model (Tri Nguyen)
28/04/2022: Self-design of physical agents or environment (Laknath Semage)
21/04/2022: -------CANCELLED--------------
14/04/2022: Physical reasoning of events in videos (Thao Le)
07/04/2022: -------CANCELLED--------------
31/03/2022: Fine-grained motion understanding (Romero Morais)
24/03/2022: Few-shot action recognition (Hoang-Anh Pham)
17/03/2022: Data encoding for quantum ML (Minh-Thang Nguyen)
10/03/2022: Causal Inference for domain adaptation (Duy-Hung Tran)
03/03/2022: -------CANCELLED--------------
24/02/2022: Theory of mind for comm and cooperation (cont.) (Dung Nguyen)
17/02/2022: Unsupervised learning of health data (Duc Nguyen)
10/02/2022: Differentiable Bayesian structure learning (Phuoc Nguyen)
03/02/2022: Hyperparameter scheduling (Hung Le)
27/01/2022: Human-in-the-loop reinforcement learning (Thommen George)
20/01/2022: Physics-informed ML (Truyen Tran)
13/01/2022: -------CANCELLED--------------
06/01/2022: -------HOLIDAY--------------
30/12/2021: -------HOLIDAY--------------
23/12/2021: -------HOLIDAY--------------
16/12/2021: Unbiased scene graph generation (Long Dang)
09/12/2021: Certified robustness via randomized smoothing (Kien Do)
02/12/2021: Systematic generalization (Kha Pham)
25/11/2021: Drug discovery using knowledge graph (Tri Nguyen)
18/11/2021: Neural causal inference (Vuong Le)
11/11/2021: Domain adaptation in RL (Laknath Semage)
04/11/2021: Contrastive learning (Yi Yang)
28/10/2021: Causal computer vision (Romero Morais)
21/10/2021: Out-of-distribution generalisation in VQA (Thao Le)
14/10/2021: Intro to quantum machine learning (Hoang-Anh Pham)
07/10/2021: Regime-switching models (Duy-Hung Tran)
30/09/2021: Theory of mind (cont.) (Dung Nguyen)
23/09/2021: Modeling medical records (Duc Nguyen)
16/09/2021: Equivariance learning (Phuoc Nguyen)
09/09/2021: Meta-RL (Hung Le)
02/09/2021: Unsupervised object-centric representation (Long Dang)
26/08/2021: -------CANCELLED. Self-study materials + recording --------------
19/08/2021: Generative memory (Kha Pham)
12/08/2021: Counter-attacking Trojans (Kien Do)
05/08/2021: -------CANCELLED--------------
29/07/2021: Smal motions (Binh Nguyen)
22/07/2021: Multimodal learning for Video QA (Long Dang)
15/07/2021: Cold-start learning in RecSys (Tri Nguyen)
08/07/2021: Causal inference in CV (Vuong Le)
01/07/2021: Neural tangent kernels (Hoang Thanh-Tung)
24/06/2021: Sim2real and model-based RL (Laknath Semage)
17/06/2021: Commonsense reasoning in CV 2 (Romero Morais)
10/06/2021: Video dialog (Hoang-Anh Pham)
03/06/2021: Unsupervised VQA (Thao Le)
27/05/2021: Unsupervised skill discovery (Yi Yang)
20/05/2021: Egocentric action modeling (Duy-Hung Tran)
13/05/2021: Theory of mind (cont.) (Dung Nguyen)
06/05/2021: Self-supervised learning in video (Duc Nguyen)
29/04/2021: Bayesian hyper-model compression (Phuoc Nguyen)
21/04/2021: Efficient transformers (Hung Le)
15/04/2021: AI until 2040 -- AAAI 2019 report (Truyen Tran)
08/04/2021: -------CANCELLED--------------
01/04/2021: Karneva++ (Kha Pham)
25/03/2021: Contrastive clustering (Kien Do)
18/03/2021: Unsupervised learning of graphs (Binh Nguyen)
11/03/2021: Object-centric neural networks (Long Dang)
04/03/2021: Interpreting graph models  (Tri Nguyen)
25/02/2021: Unsupervised relational learning (Vuong Le)
18/02/2020: Object-centric RL (Laknath Semage)
11/02/2021: Commonsense reasoning in CV (Romero Morais)
01/02/2021: Urban robotics (Ha Q. Ngo, IfU, RWTH Aachen University)
28/01/2021: Scaling laws in neural nets (Hoang-Anh Pham)
21/01/2020: -------CANCELLED--------------
14/01/2020: Contrastive learning in VQA (Thao Le)
 07/01/2021: You and your research - Richard Hamming (Truyen Tran)
31/12/2020: -------HOLIDAY--------------
24/12/2020: -------HOLIDAY--------------
17/12/2020: Soft actor-critic method in RL (Yi Yang)
10/12/2020: Deep learning 2.0 - Intro (Truyen Tran)
03/12/2020: Unsupervised learning in video (Duy-Hung Tran)
26/11/2020: Theory of mind for human-AI collaboration (Dung Nguyen)
19/11/2020: Models for sparse, irregular events (Duc Nguyen)
12/11/2020: Model compression (Phuoc Nguyen)
05/11/2020: Episodic memory in RL (Hung Le)
29/10/2020: Deep Learning 1.0 part B (Truyen Tran)
22/10/2020: Deep Learning 1.0 part A (Truyen Tran)
15/10/2020: Generative models (Kha Pham)
08/10/2020: Unsupervised representation learning for images (Kien Do)
01/10/2020: Representation learning on temporal graphs (Binh Nguyen)
24/09/2020: Unsupervised discovery in vision (Vuong Le)
17/09/2020: Logic loss for visual question answering (Cat Le)
10/09/2020: Drug-protein binding (Tri Nguyen)
03/09/2020: Object-centric reasoning (Long Dang)
27/08/2020: Human-object interaction (Romero Morais)
20/08/2020: Theoretical advances in DGMs (Hoang Thanh-Tung)
13/08/2020: Visual reasoning 4 (Thao Minh Le)
06/08/2020: Contrastive, self-supervised learning (Duy-Hung Tran)
30/07/2020: Theory-of-mind and graphs for MARL (Dung Nguyen)
23/07/2020: Irregular timing in time-series (Duc Nguyen)
16/07/2020: Learning to transform (Phuoc Nguyen)
09/07/2020: Robust machine learning (Daniel Ma, SIT)
02/07/2020: Physics-guided ML, physics reasoning (Laknath Semage)
25/06/2020: Program memories (Hung Le)
18/06/2020: Generative memory: Karneva machines (Kha Pham)
11/06/2020: AI in the Covid-19 pandemic (Truyen Tran)
04/06/2020: Machine learning in industry (Trong Nguyen & Ky Le)
28/05/2020: Graph conv net and dynamics (Binh Nguyen)
21/05/2020: Semi-supervised learning + NIPS work (Kien Do)
14/05/2020: Disentangling human behaviours in video (Vuong Le)
07/05/2020: Hierarchical human trajectories in videos (Romero Morais)
30/04/2020: MDL for Deep Generative Models (Hoang Thanh-Tung)
23/04/2020: Visual reasoning 3 (Thao Minh Le); BMVC talk (Romero Morais)
16/04/2020: Machine reasoning @A2I2, part 2 (Truyen Tran)
09/04/2020: Machine reasoning @A2I2, part 1 (Truyen Tran)
02/04/2020: Protein structure prediction via deep learning (Tri Nguyen)
26/03/2020: BERT for video (Long Dang)
19/03/2020: Human trajectory prediction (Hung Tran)
12/03/2020: Theory of mind (Dung Nguyen); ICPR talks (Duc Nguyen)
05/03/2020: RL and Optimal Transport Theory (Tang-Thanh Nguyen)
27/02/2020: Unsupervised learning in time-series (Duc Nguyen)
20/02/2020: Learning to explore (Phuoc Nguyen)
13/02/2020: Updates on memory (Hung Le)
06/02/2020: BERT family (Tin Pham)
30/01/2020: ICML'20 work (Hung Le)
23/01/2020: Domain adaptation (Kien Do)
16/01/2020: IJCAI'20 works (Phuoc, Dung, Thao)
09/01/2020: Meta-learning 3 cont. (Hoang Thanh-Tung)
02/01/2020: -------HOLIDAY--------------
26/12/2019: -------HOLIDAY--------------
19/12/2019: Meta-learning 3 (Hoang Thanh-Tung)
12/12/2019: Updates on planning (Laknath Semage)
05/12/2019: Model-based RL (Thommen George)
28/11/2019: Modern AI for drug discovery (Truyen Tran)
21/11/2019: Anomaly detection: Sequences (Duc Nguyen)
14/11/2019: Anomaly detection: Vector & Deep clustering (Duc Nguyen)
31/10/2019: Inverse RL in vision (Vuong Le)
24/10/2019: Moral AI 1 (Dung Nguyen)
17/10/2019: Visual reasoning 2 (Thao Minh Le)
10/10/2019: Hypernets and variational hyper RNN (Phuoc Nguyen)
03/10/2019: Actions prediction (Romero Morais) 
26/09/2019: Clinical QA (Tin Pham)
19/09/2019: Semantic memory (Hung Le)
12/09/2019: Geometric inference (Cat Le)
29/08/2019: AAAI'20 works (Cat,  Dung, Thao, Phuoc)
22/08/2019: Empirical AI research 3 (Truyen Tran)
15/08/2019: Human priors in video games (Thommen George)
08/08/2019: Spatio-temporal generative models (Duc Nguyen)
01/08/2019: Disentanglement for video 2 (Kien Do)
25/07/2019: Disentanglement for video 1 (Kien Do)
18/07/2019: CVPR'19 notes (Vuong Le)
11/07/2019: Theoretical DL series 1 (Hoang Thanh-Tung)
04/07/2019: Value-aligned ML 1 (Khanh Tran)
27/06/2019: Empirical AI research 2 (Truyen Tran)
20/06/2019: Memory-supported RL (Dat Nguyen)
13/06/2019: Theory of mind 2 (Dung Nguyen)
06/06/2019: Video QA (Thao Minh Le)
30/05/2019: Empirical AI research 1 (Truyen Tran)
16/05/2019: VAE for exploration (Phuoc Nguyen); NIPS19 works.
09/05/2019: Models for human behaviours in video (Romero Morais)
02/05/2019: Neural-symbolic approach to QA 2 (Tin Pham)
26/04/2019: Neural-symbolic approach to QA 1 (Tin Pham)
17/04/2019: Conversational AI 1 (Van-Khanh Tran)
11/04/2019: Disentanglement 2 (Kien Do)
05/04/2019: ODE neural nets 2 (Hoang Thanh-Tung)
28/03/2019: Neuron, RNN & memory (Hung Le)
21/03/2019: Learning to reason 1 (Truyen Tran)
14/03/2019: Video QA (Thao Minh Le); DL in smart-homes (Duc Nguyen)
08/03/2019: ML in materials science (Duong-Nguyen Nguyen, JAIST Japan)
01/03/2019: AI for matters (Truyen Tran)
22/02/2019: Memory-augmented RL 2 (Dat Nguyen)
15/02/2019: Machine theory of mind (Dung Nguyen)
11/01/2019: Continual learning in GAN & One big net (Hoang Thanh-Tung)
04/01/2019: -------HOLIDAY--------------
28/12/2018: -------HOLIDAY--------------
21/12/2018: AI/ML in 2019 and beyond: Planning session 2 (Truyen Tran)
14/12/2018: AI/ML in 2019 and beyond: Planning session 1 (Truyen Tran)
30/11/2018: Video QA (Thao Minh Le)
23/11/2018: Communication in Multiagent RL (Dung Nguyen)
16/11/2018: AI/ML in 2019 and beyond: Outlook (Truyen Tran)
09/11/2018: CVPR work (Romero Barata); AI/ML in 2018 (Truyen Tran)
02/11/2018: DL for source code modeling (Huong Ha)
26/10/2018: Memory-augmented RL 1 (Dat Nguyen)
19/10/2018: Visual reasoning 2: modularity (Tin Pham)
12/10/2018: Disentanglement via VAE (Kien Do)
05/10/2018: Spatio-temporal scene graphs (Vuong Le)
21/09/2018: MANN (Hung Le), GAN (Thanh-Tung) & Graphs (Kien Do)
14/09/2018: Graphs in genomics (Thin Nguyen), social media (Hung Nguyen)
07/09/2018: Advances in Neural Turing Machines (Truyen Tran)
31/08/2018: Universal transformer  (Adham Beykikhoshk)
24/08/2018: Learning to count  (Tin Pham)
17/08/2018: Email attachment recommendation (Binh Nguyen)
10/08/2018: Variational continual learning (Hoang Thanh-Tung)
03/08/2018: RNN, memory & attention (cont.) (Hung Le)
27/07/2018: Meta-learning 2 (Truyen Tran)
20/07/2018: Deep reinforcement learning (Phuoc Nguyen)
13/07/2018: Variational autoencoders (Budhaditya Saha)
06/07/2018: Video prediction models (Romero Morais)
29/06/2018: Graph neural nets + RL (Kien Do)
22/06/2018: Relational reasoning (Tin Pham)
15/06/2018: RNN, memory & attention (Hung Le)
08/06/2018: Deep generative models (Hoang Thanh-Tung)
01/06/2018: Deep learning for health & drug design (Truyen Tran)
18/05/2018: Scene graphs (Vuong Le)
11/05/2018: AI for science 1 (Truyen Tran)
04/05/2018: Variational encoder-decoders (Hung Le)
27/04/2018: Visual reasoning 1 (Romero Barata)
20/04/2018: Machine reasoning 1 (Kien Do)
13/04/2018: Artificial General Intelligence (AGI) 1 (Truyen Tran)
06/04/2018: GAN 2 (Hoang Thanh-Tung)
23/03/2018: Graph generative models 2 (Kien Do)
16/03/2018: Graph generative models 1 (Kien Do)
09/03/2018: The future of deep learning 4: near/medium-term (Truyen Tran)
02/03/2018: The future of deep learning 3: near/medium-term (Truyen Tran)
23/02/2018: The future of deep learning 2: near/medium-term (Truyen Tran)
09/02/2018: Graph modeling 2: Molecular models (Trang Pham)
02/02/2018: RNN (Hung Le)
19/01/2018: The future of deep learning 1: long-term (Truyen Tran)
12/01/2018: -------HOLIDAY--------------
05/12/2017: -------HOLIDAY--------------
29/12/2017: -------HOLIDAY--------------
22/12/2017: -------HOLIDAY--------------
15/12/2017: -------HOLIDAY--------------
08/12/2017: -------HOLIDAY--------------
01/12/2017: Deep learning for biomedicine 1 (Truyen Tran)
24/11/2017: Bayesian deep learning (Hoang Thanh-Tung)
10/11/2017: Action recognition on video (Vuong Le)
03/11/2017: Capsules (Trang Pham)
27/10/2017: AAAI'18 reviews review (Truyen Tran)
20/10/2017: Text + knowledge graphs for question answering (Kien Do)
13/10/2017: Learning intuitive physics from video (Truyen Tran)
29/09/2017: Object detection (Budhaditya Saha)
22/09/2017: MANN 2  (Hung Le)
15/09/2017: GAN 1  (Hoang Thanh-Tung)
08/09/2017: IJCAI-17 key papers (Kien Do, Trang Pham & Phuoc Nguyen)
01/09/2017: ICML-17 review & key papers (Truyen Tran)
04/08/2017: Meta-learning 1 (Truyen Tran)
28/07/2017: Attention mechanisms (Trang Pham)
21/07/2017: Graph modeling 1  (Kien Do)
14/07/2017: Memory-augmented neural nets (MANN) 1 (Phuoc Nguyen)