On the equivalence of Hopfield Networks and Restricted Boltzmann Machines - Adriano Barra; Alberto Bernacchia; Enrica Santucci; Pierluigi Contucci (CoRR, 2011)

On the equivalence of Hopfield networks and Boltzmann Machines. - Adriano Barra; Alberto Bernacchia; Enrica Santucci; Pierluigi Contucci (Neural Networks, 2012)

Decorrelation by Recurrent Inhibition in Heterogeneous Neural Circuits. - Alberto Bernacchia; Xiao-Jing Wang (Neural Comput., 2013)

Exact natural gradient in deep linear networks and its application to the nonlinear case. - Alberto Bernacchia; Máté Lengyel; Guillaume Hennequin (NeurIPS, 2018)

Non-reversible Gaussian processes for identifying latent dynamical structure in neural data. - Virginia Rutten; Alberto Bernacchia; Maneesh Sahani; Guillaume Hennequin (NeurIPS, 2020)

Cyclic orthogonal convolutions for long-range integration of features. - Federica Freddi; Jezabel R. Garcia; Michael Bromberg; Sepehr Jalali; Da-Shan Shiu; Alvin Chua; Alberto Bernacchia (CoRR, 2020)

Meta-learning with negative learning rates. - Alberto Bernacchia (ICLR, 2021)

Natural continual learning: success is a journey, not (just) a destination. - Ta-Chu Kao; Kristopher T. Jensen; Gido van de Ven; Alberto Bernacchia; Guillaume Hennequin (NeurIPS, 2021)

Optimal Order Simple Regret for Gaussian Process Bandits. - Sattar Vakili; Nacime Bouziani; Sepehr Jalali; Alberto Bernacchia; Da-Shan Shiu (NeurIPS, 2021)

Meta-Learning with MAML on Trees. - Jezabel R. Garcia; Federica Freddi; Feng-Ting Liao; Jamie McGowan; Tim Nieradzik; Da-Shan Shiu; Ye Tian; Alberto Bernacchia (CoRR, 2021)

How to distribute data across tasks for meta-learning? - Alexandru Cioba; Michael Bromberg; Qian Wang; Ritwik Niyogi; Georgios Batzolis; Da-Shan Shiu; Alberto Bernacchia (CoRR, 2021)

Natural continual learning: success is a journey, not (just) a destination. - Ta-Chu Kao; Kristopher T. Jensen; Alberto Bernacchia; Guillaume Hennequin (CoRR, 2021)

Uniform Generalization Bounds for Overparameterized Neural Networks. - Sattar Vakili; Michael Bromberg; Da-Shan Shiu; Alberto Bernacchia (CoRR, 2021)

How to Distribute Data across Tasks for Meta-Learning? - Alexandru Cioba; Michael Bromberg; Qian Wang; Ritwik Niyogi; Georgios Batzolis; Jezabel R. Garcia; Da-Shan Shiu; Alberto Bernacchia (AAAI, 2022)

Improved Convergence Rates for Sparse Approximation Methods in Kernel-Based Learning. - Sattar Vakili; Jonathan Scarlett; Da-Shan Shiu; Alberto Bernacchia (ICML, 2022)

Sample Complexity of Kernel-Based Q-Learning. - Sing-Yuan Yeh; Fu-Chieh Chang 001; Chang-Wei Yueh; Pei-Yuan Wu; Alberto Bernacchia; Sattar Vakili (AISTATS, 2023)

Generative Diffusion Models for Radio Wireless Channel Modelling and Sampling. - Ushnish Sengupta; Chinkuo Jao; Alberto Bernacchia; Sattar Vakili; Da-shan Shiu (GLOBECOM, 2023)

Fisher-Legendre (FishLeg) optimization of deep neural networks. - Jezabel R. Garcia; Federica Freddi; Stathi Fotiadis; Maolin Li; Sattar Vakili; Alberto Bernacchia; Guillaume Hennequin (ICLR, 2023)

Image generation with shortest path diffusion. - Ayan Das 005; Stathi Fotiadis; Anil Batra; Farhang Nabiei; Fengting Liao; Sattar Vakili; Da-Shan Shiu; Alberto Bernacchia (ICML, 2023)

Delayed Feedback in Kernel Bandits. - Sattar Vakili; Danyal Ahmed; Alberto Bernacchia; Ciara Pike-Burke (ICML, 2023)

Information Gain and Uniform Generalization Bounds for Neural Kernel Models. - Sattar Vakili; Michael Bromberg; Jezabel R. Garcia; Da-Shan Shiu; Alberto Bernacchia (ISIT, 2023)

Score Normalization for a Faster Diffusion Exponential Integrator Sampler. - Guoxuan Xia; Duolikun Danier; Ayan Das 005; Stathi Fotiadis; Farhang Nabiei; Ushnish Sengupta; Alberto Bernacchia (CoRR, 2023)

Reward-Free Kernel-Based Reinforcement Learning. - Sattar Vakili; Farhang Nabiei; Da-shan Shiu; Alberto Bernacchia (ICML, 2024)

Exact, Tractable Gauss-Newton Optimization in Deep Reversible Architectures Reveal Poor Generalization. - Davide Buffelli; Jamie McGowan; Wangkun Xu; Alexandru Cioba; Da-shan Shiu; Guillaume Hennequin; Alberto Bernacchia (NeurIPS, 2024)

Efficient Model Compression Techniques with FishLeg. - Jamie McGowan; Wei Sheng Lai; Weibin Chen; Henry Aldridge; Jools Clarke; Jezabel Garcia; Rui Xia; Yilei Liang; Guillaume Hennequin; Alberto Bernacchia (CoRR, 2024)

Near-Optimal Sample Complexity in Reward-Free Kernel-based Reinforcement Learning. - Aya Kayal; Sattar Vakili; Laura Toni; Alberto Bernacchia (AISTATS, 2025)

Bayesian Optimization from Human Feedback: Near-Optimal Regret Bounds. - Aya Kayal; Sattar Vakili; Laura Toni; Da-shan Shiu; Alberto Bernacchia (CoRR, 2025)