Alejandro Molina

1. Padé Activation Units: End-to-end Learning of Flexible Activation Functions in Deep Networks
   2019/07/15 by Alejandro Molina, Patrick Schramowski, Molina, Alejandro +3 · 18 citations
   Computer Science · #Advanced Neural Network Applications #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning and Data Classification #Neural and Evolutionary Computing (cs.NE)
2. Einsum Networks: Fast and Scalable Learning of Tractable Probabilistic\n Circuits
   2020/04/13 by Robert Peharz, Steven Lang, Peharz, Robert +15 · 14 citations
   Computer Science · #Advanced Neural Network Applications #Bayesian Modeling and Causal Inference #Explainable Artificial Intelligence (XAI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Data Classification
3. DeepDB: Learn from Data, not from Queries!
   2019/09/02 by Benjamin Hilprecht, Hilprecht, Benjamin, Andreas Schmidt +9 · 8 citations
   Computer Science · #Advanced Database Systems and Queries #Data Management and Algorithms #Data Stream Mining Techniques #Databases (cs.DB) #FOS: Computer and information sciences
4. Conditional Sum-Product Networks: Imposing Structure on Deep\n Probabilistic Architectures
   2019/05/21 by Xiaoting Shao, Alejandro Molina, Shao, Xiaoting +11 · 5 citations
   Business, Management and Accounting · Computer Science · #Bayesian Modeling and Causal Inference #Computational Drug Discovery Methods #FOS: Computer and information sciences #Graph Theory and Algorithms #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Data Classification #Product Development and Customization
5. Adaptive Rational Activations to Boost Deep Reinforcement Learning
   2021/02/18 by Quentin Delfosse, Delfosse, Quentin, Patrick Schramowski +7 · 4 citations
   Computer Science · #Evolutionary Algorithms and Applications #FOS: Computer and information sciences #Machine Learning (cs.LG) #Neural Networks and Reservoir Computing #Reinforcement Learning in Robotics