168 citations · 176 across the 5 of their papers we have counts for
5 papers
CASTILLO: Characterizing Response Length Distributions of Large Language Models
Daniel F. Perez-Ramirez, Dejan Kostic, Magnus Boman
Efficiently managing compute resources for Large Language Model (LLM) inference remains challenging due to the inherently stochastic and variable lengths of autoregressive text gen…
Robust Generalization of Graph Neural Networks for Carrier Scheduling
Daniel F. Perez-Ramirez, Carlos Pérez-Penichet, Nicolas Tsiftes +3
Battery-free sensor tags are devices that leverage backscatter techniques to communicate with standard IoT devices, thereby augmenting a network's sensing capabilities in a scalabl…
Variational Quantum Algorithms for Combinatorial Optimization
Daniel F Perez-Ramirez
The promise of quantum computing to address complex problems requiring high computational resources has long been hindered by the intrinsic and demanding requirements of quantum ha…
DeepGANTT: A Scalable Deep Learning Scheduler for Backscatter Networks
Daniel F. Perez-Ramirez, Carlos Pérez-Penichet, Nicolas Tsiftes +3
Novel backscatter communication techniques enable battery-free sensor tags to interoperate with unmodified standard IoT devices, extending a sensor network's capabilities in a scal…
Learning Combinatorial Optimization on Graphs: A Survey with Applications to Networking
Natalia Vesselinova, Rebecca Steinert, Daniel F. Perez-Ramirez +1
Existing approaches to solving combinatorial optimization problems on graphs suffer from the need to engineer each problem algorithmically, with practical problems recurring in man…