The Temporal Singularity: Time-Accelerated Simulated Civilizations and Their Implications. - Giacomo Spigler (AGI, 2018)

Meta-learnt priors slow down catastrophic forgetting in neural networks. - Giacomo Spigler (CoRR, 2019)

Convergence of regular spiking and intrinsically bursting Izhikevich neuron models as a function of discretization time with Euler method. - Harish Gunasekaran; Giacomo Spigler; Alberto Mazzoni; Enrico Cataldo; Calogero Maria Oddo (Neurocomputing, 2019)

Flatland-RL : Multi-Agent Reinforcement Learning on Trains. - Sharada Prasanna Mohanty; Erik Nygren; Florian Laurent; Manuel Schneider; Christian Scheller; Nilabha Bhattacharya; Jeremy D. Watson; Adrian Egli; Christian Eichenberger; Christian Baumberger; Gereon Vienken; Irene Sturm; et al. (CoRR, 2020)

Denoising Autoencoders for Overgeneralization in Neural Networks. - Giacomo Spigler (IEEE Trans. Pattern Anal. Mach. Intell., 2020)

Investigating Trade-offs in Utility, Fairness and Differential Privacy in Neural Networks. - Marlotte Pannekoek; Giacomo Spigler (CoRR, 2021)

Uneven Terrain Recognition Using Neuromorphic Haptic Feedback. - Sahana Prasanna; Jessica D'Abbraccio; Mariangela Filosa; Davide Ferraro; Ilaria Cesini; Giacomo Spigler; Andrea Aliperta; Filippo Dell'Agnello; Angelo Davalli; Emanuele Gruppioni; Simona Crea; Nicola Vitiello; et al. (Sensors, 2023)

Imitation of Human Motion Achieves Natural Head Movements for Humanoid Robots in an Active-Speaker Detection Task. - Bosong Ding; Murat Kirtay; Giacomo Spigler (Humanoids, 2024)

Predicting Depression and Anxiety Risk in Dutch Neighborhoods from Street-View Images. - Nin Khodorivsko; Giacomo Spigler (CoRR, 2024)

Learning secondary tool affordances of human partners using iCub robot's egocentric data. - Bosong Ding; Erhan Öztop; Giacomo Spigler; Murat Kirtay (CoRR, 2024)

Optimizing inland container shipping through reinforcement learning. - Vid Tomljenovic; Yasemin Merzifonluoglu; Giacomo Spigler (Ann. Oper. Res., 2024)

Proximal Policy Distillation. - Giacomo Spigler (Trans. Mach. Learn. Res., 2025)