Last Decade
The last decade has witnessed significant advancements in machine learning and its applications across diverse fields, focusing on improving model robustness, generalization, and explainability. Current research emphasizes developing novel architectures like spatiotemporal graph neural networks and transformers, alongside refined algorithms for tasks such as clustering categorical data and handling out-of-distribution scenarios. This progress is crucial for enhancing the reliability and trustworthiness of AI systems, impacting areas ranging from traffic forecasting and healthcare to environmental monitoring and historical analysis.
Papers
Ten Years of Generative Adversarial Nets (GANs): A survey of the state-of-the-art
Tanujit Chakraborty, Ujjwal Reddy K S, Shraddha M. Naik, Madhurima Panja, Bayapureddy Manvitha
Grandma Karl is 27 years old -- research agenda for pseudonymization of research data
Elena Volodina, Simon Dobnik, Therese Lindström Tiedemann, Xuan-Son Vu