| Problp: A framework for low-precision probabilistic inference N Shah, LI Galindez Olascoaga, W Meert, M Verhelst Proceedings of the 56th Annual Design Automation Conference 2019, 1-6, 2019 | 18 | 2019 |
| Towards Hardware-Aware Tractable Learning of Probabilistic Models LI Galindez Olascoaga, W Meert, N Shah, M Verhelst, G Van den Broeck In Advances in Neural Information Processing Systems (NeurIPS), 2019, 2019 | 15* | 2019 |
| Acceleration of probabilistic reasoning through custom processor architecture N Shah, LI Galindez Olascoaga, W Meert, M Verhelst 2020 Design, Automation & Test in Europe Conference & Exhibition (DATE), 322-325, 2020 | 10 | 2020 |
| 9.4 piu: A 248gops/w stream-based processor for irregular probabilistic inference networks using precision-scalable posit arithmetic in 28nm N Shah, LIG Olascoaga, S Zhao, W Meert, M Verhelst 2021 IEEE International Solid-State Circuits Conference (ISSCC) 64, 150-152, 2021 | 8 | 2021 |
| Dynamic sensor-frontend tuning for resource efficient embedded classification L Galindez, K Badami, J Vlasselaer, W Meert, M Verhelst IEEE Journal on Emerging and Selected Topics in Circuits and Systems 8 (4 …, 2018 | 8 | 2018 |
| Discriminative Bias for Learning Probabilistic Sentential Decision Diagrams LI Galindez Olascoaga, W Meert, N Shah, G Van den Broeck, M Verhelst Advances in Intelligent Data Analysis XVIII, 2020 | 5 | 2020 |
| Extending naive Bayes with precision-tunable feature variables for resource-efficient sensor fusion LI Galindez Olascoaga, W Meert, H Bruyninckx, M Verhelst CEUR Workshop Proceedings 1724, 23-30, 2016 | 5 | 2016 |
| DPU: DAG processing unit for irregular graphs with precision-scalable posit arithmetic in 28 nm N Shah, LIG Olascoaga, S Zhao, W Meert, M Verhelst IEEE Journal of Solid-State Circuits 57 (8), 2586-2596, 2021 | 4 | 2021 |
| On the use of bayesian networks for resource-efficient self-calibration of analog/RF ICs M Andraud, L Galindez, Y Lu, Y Makris, M Verhelst 2018 IEEE International Test Conference (ITC), 1-10, 2018 | 4 | 2018 |
| Exploiting system configurability towards dynamic accuracy-power trade-offs in sensor front-ends OLI Galindez, K Badami, VR Pamula, S Lauwereins, W Meert, M Verhelst 2016 50th Asilomar Conference on Signals, Systems and Computers, 1027-1031, 2016 | 4 | 2016 |
| On the role of hyperdimensional computing for behavioral prioritization in reactive robot navigation tasks A Menon, A Natarajan, LIG Olascoaga, Y Kim, B Benedict, JM Rabaey 2022 International Conference on Robotics and Automation (ICRA), 7335-7341, 2022 | 2 | 2022 |
| A Brain-Inspired Hierarchical Reasoning Framework for Cognition-Augmented Prosthetic Grasping LI Galindez Olascoaga, A Menon, M Ibrahim, J Rabaey Combining Learning and Reasoning: Programming Languages, Formalisms, and …, 2021 | 2* | 2021 |
| Pru: Probabilistic reasoning processing unit for resource-efficient ai NS Shah, LI Galindez Olascoaga, W Meert, M Verhelst Hot Chips: A Symposium on High Performance Chips, Date: 2019/08/18-2019/08 …, 2019 | 2 | 2019 |
| Hardware-Aware Probabilistic Circuits LI Galindez Olascoaga, W Meert, M Verhelst Hardware-Aware Probabilistic Machine Learning Models, 81-110, 2021 | 1 | 2021 |
| On hardware-aware probabilistic frameworks for resource constrained embedded applications LIG Olascoaga, W Meert, N Shah, G Van den Broeck, M Verhelst 2019 Fifth Workshop on Energy Efficient Machine Learning and Cognitive …, 2019 | 1 | 2019 |
| Brain-inspired Multi-level Control of an Assistive Prosthetic Hand through EMG Task Recognition A Menon, LIG Olascoaga, N Shakouri, J Ruffing, V Balanaga, JM Rabaey 2022 IEEE Biomedical Circuits and Systems Conference (BioCAS), 384-388, 2022 | | 2022 |
| Hardware-aware Probabilistic Machine Learning Models: Learning, Inference and Use Cases LIG Olascoaga, W Meert, M Verhelst Springer Nature, 2021 | | 2021 |
| Hardware-aware Probabilistic Machine Learning Models: Learning, Inference and Use Cases LIG Olascoaga, W Meert, M Verhelst Springer Nature, 2021 | | 2021 |
| Run-Time Strategies LI Galindez Olascoaga, W Meert, M Verhelst Hardware-Aware Probabilistic Machine Learning Models, 111-137, 2021 | | 2021 |
| Hardware-Aware Bayesian Networks for Sensor Front-End Quality Scaling LI Galindez Olascoaga, W Meert, M Verhelst Hardware-Aware Probabilistic Machine Learning Models, 55-79, 2021 | | 2021 |
Marian VerhelstMicas - ESAT - KU Leuven, BelgiumVerified email at esat.kuleuven.be
