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awesome-deep-causal-learning
A curated list of awesome deep causal learning methods since 2018
https://github.com/huckiyang/awesome-deep-causal-learning
Last synced: 3 days ago
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Causal Inference
- Causal bandits: Learning good interventions via causal inference - |NeurIPS, 2016|
- One-shot learning by inverting a compositional causal process - | NeurIPS 2013 |
- Long-Tailed Classification by Keeping the Good and Removing the Bad Momentum Causal Effect - Tailed-Recognition.pytorch)|NeurIPS 2020|
- Causal Intervention for Weakly-Supervised Semantic Segmentation - NJUST/CONTA)|NeurIPS 2020|
- A Meta-Transfer Objective for Learning to Disentangle Causal Mechanisms - 1901-10912/A-Meta-Transfer-Objective-For-Learning-To-Disentangle-Causal-Mechanisms)|ICLR 2020|
- Causal Induction from Visual Observations for Goal Directed Tasks - |arxiv 2019|
- Granger-causal attentive mixtures of experts: Learning important features with neural networks - |AAAI 2019|
- Causal bandits: Learning good interventions via causal inference - |NeurIPS, 2016|
- Learning granger causality for hawkes processes - |ICML 2016|
- One-shot learning by inverting a compositional causal process - | NeurIPS 2013 |
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Causal Reinforcement Learning
- Training a Resilient Q-network against Observational Interference - Causal-Q-Network)|AAAI 2022|
- Off-policyevaluation in infinite-horizon reinforcement learning with latent confounders - |AISTATS 2021|
- Off-policyevaluation in infinite-horizon reinforcement learning with latent confounders - |AISTATS 2021|
- Training a Resilient Q-network against Observational Interference - Causal-Q-Network)|AAAI 2022|
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Treatment Effect Estimation
- Estimating identifiable causal effects through double machine learning - |AAAI 2021|
- Causal effect inference with deep latent-variable models - Amsterdam/CEVAE)|NIPS 2017|
- Estimating individual treatment effect: generalization bounds and algorithms
- Towards a learning theory of cause-effect inference - |ICML 2015|
- Estimating identifiable causal effects through double machine learning - |AAAI 2021|
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Vision
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- Interventional Few-Shot Learning - zhongqi/ifsl)|NeurIPS 2020|
- Counterfactual Vision and Language Learning - |CVPR 2020|
- Towards Causal VQA: Revealing and Reducing Spurious Correlations by Invariant and Covariant Semantic Editing
- Two Causal Principles for Improving Visual Dialog - principles)|CVPR 2020|
- Unbiased Scene Graph Generation from Biased Training - Graph-Benchmark.pytorch)|CVPR 2020|
- When Causal Intervention Meets Adversarial Examples and Image Masking for Deep Neural Networks - Intervention-AE-wAdvImg)|ICIP 2019|
- Discovering causal signals in images - Paz et al.|code withdrawn from author|CVPR 2017|
- Causal graph-based video segmentation - |ICIP 2013|
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