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Reduced Precision Strategies for Deep Learning : A High Energy Physics Generative Adversarial Network Use Case2021 RWTH Publications (RWTH Aachen) conference-paper Computer Science Advanced Neural Network Applications Open access
Florian Rehm, Sofia Vallecorsa, Vikram A. Saletore, Hans Pabst, Adel Chaibi, Valeriu Codreanu, +2 more
12citations -
Accelerating Deep Learning Inference in Constrained Embedded Devices Using Hardware Loops and a Dot Product Unit2020 IEEE Access article Computer Science Parallel Computing and Optimization Techniques Open access cited by 1 patent
Jure Vreča, Karl J. X. Sturm, Ernest Gungl, Farhad Merchant, Paolo Bientinesi, Rainer Leupers, +1 more
17citations -
Efficient Inference in Bayesian Networks with Continuous Variables A Discretization and Knowledge Compilation Approach2023 SSRN Electronic Journal preprint Computer Science Bayesian Modeling and Causal Inference Open access
Maarten Vonk, Sebastiaan Brand, Ninoslav Malekovic, Thomas Bäck, Alfons Laarman, Anna V. Kononova
2citations -
FPGA-based Deep Learning Inference Accelerators: Where Are We Standing?2023 ACM Transactions on Reconfigurable Technology and Systems article Computer Science Embedded Systems Design Techniques Open access
Anouar Nechi, Lukas Groth, Saleh Mulhem, Farhad Merchant, Rainer Buchty, Mladen Bereković
73citations -
Bayesian network imputation methods applied to multi-omics data identify putative causal relationships in a type 2 diabetes dataset containing incomplete data: An IMI DIRECT Study
Richard A. J. Howey, Jonathan Adam, Jerzy Adamski, Natalie N. Atabaki, Søren Brunak, Piotr Jaroslaw Chmura, +32 more
1citations -
Parallel Adaptive Multi-Objective Evolutionary Learning of Discretized Bayesian Network Classifiers for Clinical Data2026 Genetic and Evolutionary Computation Conference Companion (GECCO Companion) conference-paper Computer Science Bayesian Modeling and Causal Inference Open access
Damy M. F. Ha, Thalea Schlender, Yvette M. van der Linden, Peter A. N. Bosman, Tanja Alderliesten
0citations -
ExPAN(N)D: Exploring Posits for Efficient Artificial Neural Network Design in FPGA-Based Systems2020 arXiv (Cornell University) preprint Computer Science Numerical Methods and Algorithms Open access
Suresh Nambi, Salim Ullah, Siva Satyendra Sahoo, Aditya Lohana, Farhad Merchant, Akash S. Kumar
4citations -
Unified field theoretical approach to deep and recurrent neuronal networks2022 Journal of Statistical Mechanics Theory and Experiment article Computer Science Gaussian Processes and Bayesian Inference Open access
Kai Segadlo, Bastian Epping, Alexander van Meegen, David Dahmen, Moritz Helias
17citations