P. Baldi

Publications290
h-index73
Citations24,416
Highly Influential Citations1,624
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Assessing the accuracy of prediction algorithms for classification: an overview
TLDR
We provide a unified overview of methods that currently are widely used to assess the accuracy of prediction algorithms, from raw percentages, quadratic error measures and other distances, and correlation coefficients, to information theoretic measures such as relative entropy and mutual information. Expand
  • 1,752
  • 166
  • PDF
Bayesian surprise attracts human attention
  • L. Itti, P. Baldi
  • Computer Science, Psychology
  • Vision Research
  • 5 December 2005
TLDR
We propose a formal Bayesian definition of surprise to capture subjective aspects of sensory information. Expand
  • 1,256
  • 113
  • PDF
A Bayesian framework for the analysis of microarray expression data: regularized t -test and statistical inferences of gene changes
TLDR
MOTIVATION DNA microarrays are now capable of providing genome-wide patterns of gene expression across many conditions. Expand
  • 1,688
  • 110
  • PDF
Neural networks and principal component analysis: Learning from examples without local minima
TLDR
We consider the problem of learning from examples in layered linear feed-forward neural networks using optimization methods such as back propagation, with respect to the usual quadratic error function E of the connection weights. Expand
  • 1,173
  • 75
Prediction of protein stability changes for single‐site mutations using support vector machines
Accurate prediction of protein stability changes resulting from single amino acid mutations is important for understanding protein structures and designing new proteins. We use support vector… Expand
  • 537
  • 57
  • PDF
SCRATCH: a protein structure and structural feature prediction server
TLDR
SCRATCH is a server for predicting protein tertiary structure and structural features. Expand
  • 748
  • 51
  • PDF
Improving the prediction of protein secondary structure in three and eight classes using recurrent neural networks and profiles
TLDR
We use an ensemble of bidirectional recurrent neural network architectures, PSI‐BLAST‐derived profiles, and a large nonredundant training set to derive two new predictors for secondary structure classification. Expand
  • 746
  • 44
  • PDF
A principled approach to detecting surprising events in video
  • L. Itti, P. Baldi
  • Computer Science
  • IEEE Computer Society Conference on Computer…
  • 20 June 2005
TLDR
We present a new theory of sensory surprise, which provides a principled and computable shortcut to important information. Expand
  • 412
  • 42
  • PDF
An enhanced MITOMAP with a global mtDNA mutational phylogeny
TLDR
The MITOMAP data system for the human mitochondrial genome has been greatly enhanced by the addition of a navigable mutational mitochondrial DNA (mtDNA) phylogenetic tree of ∼3000 mtDNA coding region sequences plus expanded pathogenic mutation tables and a nuclear-mtDNA pseudogene data base. Expand
  • 533
  • 37
  • PDF
SSpro/ACCpro 5: almost perfect prediction of protein secondary structure and relative solvent accessibility using profiles, machine learning and structural similarity
TLDR
MOTIVATION Accurately predicting protein secondary structure and relative solvent accessibility is important for the study of protein evolution, structure and function and as a component of protein 3D structure prediction pipelines. Expand
  • 223
  • 35
  • PDF