All sources cited or reviewed
This is a list of all sources we have used in the TransferLab, with links to the referencing content and metadata, like accompanying code, videos, etc. If you think we should look at something, drop us a line
References
[Sif17A]
Anomaly Detection in Streams with Extreme Value Theory,
[Van14R]
Robust Kernel Density Estimation by Scaling and Projection in Hilbert Space,
[Wu21C]
Current Time Series Anomaly Detection Benchmarks are Flawed and are Creating the Illusion of Progress,
[Bet18C]
A Conceptual Introduction to Hamiltonian Monte Carlo,
[Roc20S]
Solving Schrödinger’s equation with Deep Learning,
[Bis06P]
Pattern recognition and machine learning,
[Nac20R]
Reinforcement Learning via Fenchel-Rockafellar Duality,
[Kob20N]
Normalizing Flows: An Introduction and Review of Current Methods,
[Maz20L]
Leveraging exploration in off-policy algorithms via normalizing flows,
[Pap19N]
Normalizing Flows for Probabilistic Modeling and Inference,
[War19I]
Improving Exploration in Soft-Actor-Critic with Normalizing Flows Policies,
[Fuj19O]
Off-Policy Deep Reinforcement Learning without Exploration,
[Kum19S]
Stabilizing Off-Policy Q-Learning via Bootstrapping Error Reduction,
[Wu19B]
Behavior Regularized Offline Reinforcement Learning,
[Sid16F]
Finite Sample Complexity of Rare Pattern Anomaly Detection,
[Fer19S]
Setting decision thresholds when operating conditions are uncertain,
[Kum18T]
Trainable Calibration Measures for Neural Networks from Kernel Mean Embeddings,
[Lin17F]
Focal Loss for Dense Object Detection,
[Nic05P]
Predicting good probabilities with supervised learning,
[Per17R]
Regularizing Neural Networks by Penalizing Confident Output Distributions,
[Pla99P]
Probabilistic Outputs for Support Vector Machines and Comparisons to Regularized Likelihood Methods,
[Rag18B]
Behaviour Policy Estimation in Off-Policy Policy Evaluation: Calibration Matters,
[Ach18E]
Emergence of Invariance and Disentanglement in Deep Representations,