Exploiting system configurability towards dynamic accuracy-power trade-offs in sensor front-ends. - Laura Isabel Galindez Olascoaga; Komail M. H. Badami; V. Rajesh Pamula 002; Steven Lauwereins; Wannes Meert; Marian Verhelst (ACSSC, 2016)

Extending Naive Bayes with Precision-tunable Feature Variables for Resource-efficient Sensor Fusion. - Laura Isabel Galindez Olascoaga; Wannes Meert; Herman Bruyninckx; Marian Verhelst (AI-IoT@ECAI, 2016)

Feature noise tuning for resource efficient Bayesian Network Classifiers. - Laura Isabel Galindez Olascoaga; Jonas Vlasselaer; Wannes Meert; Marian Verhelst (ESANN, 2018)

On the use of Bayesian Networks for Resource-Efficient Self-Calibration of Analog/RF ICs. - Martin Andraud; Laura Isabel Galindez Olascoaga; Yichuan Lu; Yiorgos Makris; Marian Verhelst (ITC, 2018)

Dynamic Sensor-Frontend Tuning for Resource Efficient Embedded Classification. - Laura Isabel Galindez Olascoaga; Komail M. H. Badami; Jonas Vlasselaer; Wannes Meert; Marian Verhelst (IEEE J. Emerg. Sel. Topics Circuits Syst., 2018)

ProbLP: A framework for low-precision probabilistic inference. - Nimish Shah; Laura Isabel Galindez Olascoaga; Wannes Meert; Marian Verhelst (DAC, 2019)

On Hardware-Aware Probabilistic Frameworks for Resource Constrained Embedded Applications. - Laura Isabel Galindez Olascoaga; Wannes Meert; Nimish Shah; Guy Van den Broeck; Marian Verhelst (EMC2@NeurIPS, 2019)

Towards Hardware-Aware Tractable Learning of Probabilistic Models. - Laura Isabel Galindez Olascoaga; Wannes Meert; Nimish Shah; Marian Verhelst; Guy Van den Broeck (NeurIPS, 2019)

Acceleration of probabilistic reasoning through custom processor architecture. - Nimish Shah; Laura Isabel Galindez Olascoaga; Wannes Meert; Marian Verhelst (DATE, 2020)

Discriminative Bias for Learning Probabilistic Sentential Decision Diagrams. - Laura Isabel Galindez Olascoaga; Wannes Meert; Nimish Shah; Guy Van den Broeck; Marian Verhelst (IDA, 2020)

Dynamic Complexity Tuning for Hardware-Aware Probabilistic Circuits. - Laura Isabel Galindez Olascoaga; Wannes Meert; Nimish Shah; Marian Verhelst (IoT Streams/ITEM@PKDD/ECML, 2020)

9.4 PIU: A 248GOPS/W Stream-Based Processor for Irregular Probabilistic Inference Networks Using Precision-Scalable Posit Arithmetic in 28nm. - Nimish Shah; Laura Isabel Galindez Olascoaga; Shirui Zhao; Wannes Meert; Marian Verhelst (ISSCC, 2021)

DPU: DAG Processing Unit for Irregular Graphs with Precision-Scalable Posit Arithmetic in 28nm. - Nimish Shah; Laura Isabel Galindez Olascoaga; Shirui Zhao; Wannes Meert; Marian Verhelst (CoRR, 2021)

Brain-inspired Multi-level Control of an Assistive Prosthetic Hand through EMG Task Recognition. - Alisha Menon; Laura Isabel Galindez Olascoaga; Niki Shakouri; Jennifer Ruffing; Vamshi Balanaga; Jan M. Rabaey (BioCAS, 2022)

On the Role of Hyperdimensional Computing for Behavioral Prioritization in Reactive Robot Navigation Tasks. - Alisha Menon; Anirudh Natarajan; Laura Isabel Galindez Olascoaga; Youbin Kim; Braeden C. Benedict; Jan M. Rabaey (ICRA, 2022)

DPU: DAG Processing Unit for Irregular Graphs With Precision-Scalable Posit Arithmetic in 28 nm. - Nimish Shah; Laura Isabel Galindez Olascoaga; Shirui Zhao; Wannes Meert; Marian Verhelst (IEEE J. Solid State Circuits, 2022)

Shared Control of Assistive Robots through User-intent Prediction and Hyperdimensional Recall of Reactive Behavior. - Alisha Menon; Laura Isabel Galindez Olascoaga; Vamshi Balanaga; Anirudh Natarajan; Jennifer Ruffing; Ryan Ardalan; Jan M. Rabaey (ICRA, 2023)

A Phenomenological AI Foundation Model for Physical Signals. - Jaime Lien; Laura Isabel Galindez Olascoaga; Hasan Dogan; Nicholas Gillian; Brandon Barbello; Leonardo Giusti; Ivan Poupyrev (CoRR, 2024)