61 citations · 144 across the 21 of their papers we have counts for
21 papers
Beyond Worst-Case Branching: Quantum Tree Search via Amplitude Amplification
Andreas Wichert
In this work, we investigate quantum tree search via amplitude amplification. Amplitude amplification generalizes Grover's algorithm by replacing the Hadamard initialization with a…
Competitive learning to generate sparse representations for associative memory
Luis Sacouto, Andreas Wichert
One of the most well established brain principles, hebbian learning, has led to the theoretical concept of neural assemblies. Based on it, many interesting brain theories have spaw…
The smooth output assumption, and why deep networks are better than wide ones
Luis Sa-Couto, Jose Miguel Ramos, Andreas Wichert
When several models have similar training scores, classical model selection heuristics follow Occam's razor and advise choosing the ones with least capacity. Yet, modern practice w…
Understanding the double descent curve in Machine Learning
Luis Sa-Couto, Jose Miguel Ramos, Miguel Almeida +1
The theory of bias-variance used to serve as a guide for model selection when applying Machine Learning algorithms. However, modern practice has shown success with over-parameteriz…
Multi-level Data Representation For Training Deep Helmholtz Machines
Jose Miguel Ramos, Luis Sa-Couto, Andreas Wichert
A vast majority of the current research in the field of Machine Learning is done using algorithms with strong arguments pointing to their biological implausibility such as Backprop…
Can a Hebbian-like learning rule be avoiding the curse of dimensionality in sparse distributed data?
Maria Osório, Luís Sa-Couto, Andreas Wichert
It is generally assumed that the brain uses something akin to sparse distributed representations. These representations, however, are high-dimensional and consequently they affect…
Classification and Generation of real-world data with an Associative Memory Model
Rodrigo Simas, Luis Sa-Couto, Andreas Wichert
Drawing from memory the face of a friend you have not seen in years is a difficult task. However, if you happen to cross paths, you would easily recognize each other. The biologica…
Using brain inspired principles to unsupervisedly learn good representations for visual pattern recognition
Luis Sa-Couto, Andreas Wichert
Although deep learning has solved difficult problems in visual pattern recognition, it is mostly successful in tasks where there are lots of labeled training data available. Furthe…
An Investigation of Interpretability Techniques for Deep Learning in Predictive Process Analytics
Catarina Moreira, Renuka Sindhgatta, Chun Ouyang +2
This paper explores interpretability techniques for two of the most successful learning algorithms in medical decision-making literature: deep neural networks and random forests. W…
Introducing Quantum-Like Influence Diagrams for Violations of the Sure Thing Principle
Catarina Moreira, Andreas Wichert
It is the focus of this work to extend and study the previously proposed quantum-like Bayesian networks to deal with decision-making scenarios by incorporating the notion of maximu…
The Dutch's Real World Financial Institute: Introducing Quantum-Like Bayesian Networks as an Alternative Model to deal with Uncertainty
Catarina Moreira, Emmanuel Haven, Sandro Sozzo +1
In this work, we analyse and model a real life financial loan application belonging to a sample bank in the Netherlands. The log is robust in terms of data, containing a total of 2…
Are Quantum Models for Order Effects Quantum?
Catarina Moreira, Andreas Wichert
The application of principles of Quantum Mechanics in areas outside of physics has been getting increasing attention in the scientific community in an emergent discipline called Qu…
The Relation Between Acausality and Interference in Quantum-Like Bayesian Networks
Catarina Moreira, Andreas Wichert
We analyse a quantum-like Bayesian Network that puts together cause/effect relationships and semantic similarities between events. These semantic similarities constitute acausal co…
On Projection Based Operators in Lp space for Exact Similarity Search
Andreas Wichert, Catarina Moreira
We investigate exact indexing for high dimensional Lp norms based on the 1-Lipschitz property and projection operators. The orthogonal projection that satisfies the 1-Lipschitz pro…
Quantum Iterative Deepening with an application to the Halting problem
Luís Tarrataca, Andreas Wichert
Classical models of computation traditionally resort to halting schemes in order to enquire about the state of a computation. In such schemes, a computational process is responsibl…
A Quantum Production Model
Luís Tarrataca, Andreas Wichert
The production system is a theoretical model of computation relevant to the artificial intelligence field allowing for problem solving procedures such as hierarchical tree search.…
Can Quantum Entanglement Detection Schemes Improve Search?
Luís Tarrataca, Andreas Wichert
Quantum computation, in particular Grover's algorithm, has aroused a great deal of interest since it allows for a quadratic speedup to be obtained in search procedures. Classical s…
Tree Search and Quantum Computation
Luís Tarrataca, Andreas Wichert
Traditional tree search algorithms supply a blueprint for modeling problem solving behaviour. A diverse spectrum of problems can be formulated in terms of tree search. Quantum comp…
Interference Effects in Quantum Belief Networks
Catarina Moreira, Andreas Wichert
Probabilistic graphical models such as Bayesian Networks are one of the most powerful structures known by the Computer Science community for deriving probabilistic inferences. Howe…
Finding Academic Experts on a MultiSensor Approach using Shannon's Entropy
Catarina Moreira, Andreas Wichert
Expert finding is an information retrieval task concerned with the search for the most knowledgeable people, in some topic, with basis on documents describing peoples activities. T…
Binary Willshaw learning yields high synaptic capacity for long-term familiarity memory
João Sacramento, Andreas Wichert
We investigate from a computational perspective the efficiency of the Willshaw synaptic update rule in the context of familiarity discrimination, a binary-answer, memory-related ta…