{
  "originalData": {
    "name": "Al in Drug Discovery Companies Focus on Oncology: Leadership by Funding Level",
    "data": {
      "Machine Learning": {
        "Reinforcement Learning": {
          "Classical RL": {
            "Q-Learning": "1992",
            "SARSA (State-Action-Reward-State-Action)": "1994",
            "Policy Gradient Methods": "1999"
          },
          "Deep RL": {
            "Trust Region Policy Optimization (TRPO)": "2015",
            "Deep Q-Network (DQN)": "2015",
            "Double DQN": "2016",
            "Dueling DQN": "2016",
            "Advantage Actor-Critic (A2C)": "2016",
            "Asynchronous Advantage Actor-Critic (A3C)": "2016",
            "Soft Actor-Critic (SAC)": "2018"
          }
        },
        "Supervised/Unsupervised Learning": {
          "Neural Network Based Algorithms": {
            "Siamese Neural Networks": {
              "Basic Siamese network": "2005",
              "Triple network": "2015",
              "Quadruple network": "2017",
              "RNN-based Siamese network": "2017",
              "Multi-view Siamese network": "2018",
              "Pseudo Siamese network": "2018",
              "GNN-based Siamese network": "2019",
              "Siamese GAN": "2019",
              "Manifold-based Siamese network": "2019",
              "Cross-modal Siamese network": "2019",
              "DenseDisp": "2020"
            },
            "Graph neural networks": {
              "Recurrent Graph Neural Networks": {
                "Graph Neural Network": "2005",
                "Graph Echo State Networks (GraphESN)": "2010",
                "Graph Attention Network": "2017"
              },
              "Convolutional Graph Neural Networks": {
                "Spectral-based Convolutional Graph Neural Network": "2014",
                "Diffusion-convolutional Graph Neural Network": "2016"
              },
              "Graph Autoencoders": {
                "Network Embeddings": {
                  "Graph Autoencoder": "2016",
                  "Variational Graph Auto-Encoders": "2016",
                  "Adversarially Regularized Graph Autoencoder": "2018"
                },
                "Graph Generation": {
                  "GraphRNN": "2018",
                  "GraphVAE": "2018",
                  "NetGAN": "2018"
                }
              },
              "Spatial-temporal Graph Neural Networks": {
                "Structural-RNN": "2016",
                "Graph WaveNet": "2018",
                "Spatio-Temporal Graph Convolutional Networks": "2018",
                "Attention Based Spatial-Temporal Graph Convolutional Networks": "2019"
              }
            },
            "Language Models (LM)": {
              "Statistical Language Models": {
                "Statistical Language model": "1998"
              },
              "Neural Language Models": {
                "Neural language model": "2003"
              },
              "Pre-trained Language Models": {
                "Embeddings from Language Models (ELMo)": "2018",
                "RoBERTa (Robustly Optimized BERT Pretraining Approach)": "2019",
                "Bidirectional Encoder Representations from Transformers (BERT)": "2018",
                "GPT (Generative Pre-trained Transformer)": "2018",
                "GPT-2": "2019",
                "BART": "2019"
              },
              "Large Language Models": {
                "T5 (Text-to-Text Transfer Transformer)": "2019",
                "GPT-3": "2020",
                "LaMDA": "2022",
                "PaLM": "2022",
                "Galactica": "2022",
                "GPT-4": "2023",
                "LLaMA": "2023"
              }
            },
            "Autoencoders": {
              "Vanilla Autoencoder": "1987",
              "Denoising Autoencoder": "2008",
              "Convolutional Autoencoder": "2011",
              "Contractive Autoencoder": "2011",
              "Variational Autoencoder": "2013",
              "Adversarial Autoencoder": "2015"
            },
            "Diffusion models": {
              "Diffusion Probabilistic Model": "2015",
              "Noise-conditioned Score Network": "2019",
              "Denoising diffusion probabilistic model": "2020",
              "Latent Diffusion Model": "2022"
            },
            "Generative adversarial networks": {
              "Vanilla GAN": "2014",
              "Conditional GAN": "2014",
              "Wasserstein GAN (WGAN)": "2017",
              "CycleGAN": "2017",
              "Progressive GAN": "2017",
              "StarGAN": "2017"
            },
            "Transformers": {
              "Vanilla Transformer": "2017",
              "BERT (Bidirectional Encoder Representations from Transformers)": "2018",
              "XLNet": "2019"
            },
            "Recurrent neural networks": {
              "Jordan Network": "1986",
              "Elman Network": "1990",
              "Long Short-Term Memory (LSTM)": "1997",
              "Bidirectional RNN (BRNN)": "1997",
              "Echo State Network (ESN)": "2002",
              "Gated Recurrent Unit (GRU)": "2014",
              "RNNsearch": "2014",
              "Hierarchical RNN (HRNN)": "2015",
              "Recurrent Convolutional Neural Network (RCNN)": "2015",
              "UGRNN": "2015",
              "QRNN": "2016",
              "GNMT": "2016",
              "AWD-LSTM": "2018",
              "SRU": "2018"
            },
            "Convolutional Neural Networks (ConvNets, CNNs)": {
              "Video Processing": {
                "3D CNN": "2012",
                "Two-Steam CNN": "2014",
                "Two-Steam CNN with Fusion": "2016",
                "Temporal Segment CNN": "2016",
                "You Look Only Once (YOLO)": "2016",
                "R(2+1)D": "2018"
              },
              "Image Processing Networks": {
                "LeNet": "1998",
                "AlexNet": "2012",
                "VGG": "2014",
                "GoogLeNet (Inception)": "2014",
                "ResNet": "2015",
                "DenseNet": "2016",
                "MobileNet": "2017",
                "ImageNet": "2017",
                "EfficientNet": "2019",
                "EfficientNetV2": "2020",
                "Vision Transformer (ViT)": "2020",
                "ResNeSt": "2020",
                "Swin Transformer": "2021",
                "CrossViT": "2021"
              }
            },
            "Feedforward neural networks": {
              "Single-layer perceptron": "1958",
              "Multi-layer perceptron": "1965"
            }
          },
          "Classical ML": {
            "Instance-based ML": {
              "k-Nearest Neighbors (kNN)": "1951",
              "Memory-Based Reasoning (MBR)": "1991",
              "Case-Based Reasoning": "1993"
            },
            "Non-instance-based ML": {
              "Bayesian Algorithms": {
                "Regression": {
                  "Bayesian Linear Regression": "1992",
                  "Gaussian process regression": "2006",
                  "Bayesian CART": "1998"
                },
                "Clusterization": {
                  "Gaussian Mixture Model": "1977"
                }
              },
              "Non-Bayesian Algorithms": {
                "Clusterization": {
                  "K-means": "1967",
                  "Hierarchical clustering": "1963",
                  "DBSCAN": "1996",
                  "Spectral clustering": "2001"
                },
                "Regression": {
                  "Ensembles": {
                    "Boosting": {
                      "CatBoost": "2018",
                      "LightGBM": "2017",
                      "XGBoost": "2016",
                      "Gradient Tree Boosting": "2001",
                      "AdaBoost": "1995"
                    },
                    "Stacking": "1992",
                    "Bagging": {
                      "Rotation Forest": "2006",
                      "Random Forest": "2001"
                    }
                  },
                  "Support Vector Machine (SVM)": "1995",
                  "Decision Trees": {
                    "Classification and Regression Trees (CART)": "1984",
                    "ID3": "1986",
                    "C4.5": "1993"
                  },
                  "Linear  Regressors": {
                    "Linear Regression": "1869",
                    "Logistic Regression": "1958",
                    "Ridge Regression": "1970",
                    "Lasso Regression": "1996",
                    "Elastic Net": "2005",
                    "Partial least-squares regression": "1986",
                    "Principal Components Regression": "1982"
                  }
                }
              }
            }
          }
        }
      }
    }
  }
}